Overview

Brought to you by YData

Dataset statistics

Number of variables122
Number of observations307511
Missing cells0
Missing cells (%)0.0%
Total size in memory285.1 MiB
Average record size in memory972.0 B

Variable types

Numeric107
Text15

Alerts

AMT_INCOME_TOTAL is highly skewed (γ1 = 391.5596541) Skewed
FLAG_MOBIL is highly skewed (γ1 = -554.5367436) Skewed
FLAG_CONT_MOBILE is highly skewed (γ1 = -23.08117235) Skewed
YEARS_BEGINEXPLUATATION_AVG is highly skewed (γ1 = -21.74476589) Skewed
NONLIVINGAPARTMENTS_AVG is highly skewed (γ1 = 27.81539184) Skewed
YEARS_BEGINEXPLUATATION_MODE is highly skewed (γ1 = -20.68616897) Skewed
NONLIVINGAPARTMENTS_MODE is highly skewed (γ1 = 29.12609052) Skewed
YEARS_BEGINEXPLUATATION_MEDI is highly skewed (γ1 = -21.82538695) Skewed
NONLIVINGAPARTMENTS_MEDI is highly skewed (γ1 = 28.05803955) Skewed
FLAG_DOCUMENT_2 is highly skewed (γ1 = 153.7918174) Skewed
FLAG_DOCUMENT_4 is highly skewed (γ1 = 110.8943644) Skewed
FLAG_DOCUMENT_7 is highly skewed (γ1 = 72.17410795) Skewed
FLAG_DOCUMENT_10 is highly skewed (γ1 = 209.5890537) Skewed
FLAG_DOCUMENT_12 is highly skewed (γ1 = 392.1147791) Skewed
FLAG_DOCUMENT_15 is highly skewed (γ1 = 28.69933309) Skewed
FLAG_DOCUMENT_17 is highly skewed (γ1 = 61.21414027) Skewed
FLAG_DOCUMENT_19 is highly skewed (γ1 = 40.95613431) Skewed
FLAG_DOCUMENT_20 is highly skewed (γ1 = 44.3648968) Skewed
FLAG_DOCUMENT_21 is highly skewed (γ1 = 54.61293914) Skewed
AMT_REQ_CREDIT_BUREAU_DAY is highly skewed (γ1 = 29.08157716) Skewed
AMT_REQ_CREDIT_BUREAU_QRT is highly skewed (γ1 = 141.4009149) Skewed
SK_ID_CURR has unique values Unique
TARGET has 282686 (91.9%) zeros Zeros
CNT_CHILDREN has 215371 (70.0%) zeros Zeros
FLAG_EMP_PHONE has 55386 (18.0%) zeros Zeros
FLAG_WORK_PHONE has 246203 (80.1%) zeros Zeros
FLAG_PHONE has 221080 (71.9%) zeros Zeros
FLAG_EMAIL has 290069 (94.3%) zeros Zeros
REG_REGION_NOT_LIVE_REGION has 302854 (98.5%) zeros Zeros
REG_REGION_NOT_WORK_REGION has 291899 (94.9%) zeros Zeros
LIVE_REGION_NOT_WORK_REGION has 295008 (95.9%) zeros Zeros
REG_CITY_NOT_LIVE_CITY has 283472 (92.2%) zeros Zeros
REG_CITY_NOT_WORK_CITY has 236644 (77.0%) zeros Zeros
LIVE_CITY_NOT_WORK_CITY has 252296 (82.0%) zeros Zeros
BASEMENTAREA_AVG has 14745 (4.8%) zeros Zeros
COMMONAREA_AVG has 8442 (2.7%) zeros Zeros
ELEVATORS_AVG has 249609 (81.2%) zeros Zeros
LANDAREA_AVG has 15600 (5.1%) zeros Zeros
NONLIVINGAPARTMENTS_AVG has 268063 (87.2%) zeros Zeros
NONLIVINGAREA_AVG has 58735 (19.1%) zeros Zeros
BASEMENTAREA_MODE has 16598 (5.4%) zeros Zeros
COMMONAREA_MODE has 9690 (3.2%) zeros Zeros
ELEVATORS_MODE has 253389 (82.4%) zeros Zeros
FLOORSMAX_MODE has 3415 (1.1%) zeros Zeros
LANDAREA_MODE has 17453 (5.7%) zeros Zeros
NONLIVINGAPARTMENTS_MODE has 272769 (88.7%) zeros Zeros
NONLIVINGAREA_MODE has 67126 (21.8%) zeros Zeros
BASEMENTAREA_MEDI has 14991 (4.9%) zeros Zeros
COMMONAREA_MEDI has 8691 (2.8%) zeros Zeros
ELEVATORS_MEDI has 250917 (81.6%) zeros Zeros
LANDAREA_MEDI has 15919 (5.2%) zeros Zeros
NONLIVINGAPARTMENTS_MEDI has 269611 (87.7%) zeros Zeros
NONLIVINGAREA_MEDI has 60954 (19.8%) zeros Zeros
EMERGENCYSTATE_MODE has 145755 (47.4%) zeros Zeros
OBS_30_CNT_SOCIAL_CIRCLE has 164931 (53.6%) zeros Zeros
DEF_30_CNT_SOCIAL_CIRCLE has 272345 (88.6%) zeros Zeros
OBS_60_CNT_SOCIAL_CIRCLE has 165687 (53.9%) zeros Zeros
DEF_60_CNT_SOCIAL_CIRCLE has 281742 (91.6%) zeros Zeros
DAYS_LAST_PHONE_CHANGE has 37672 (12.3%) zeros Zeros
FLAG_DOCUMENT_2 has 307498 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_3 has 89171 (29.0%) zeros Zeros
FLAG_DOCUMENT_4 has 307486 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_5 has 302863 (98.5%) zeros Zeros
FLAG_DOCUMENT_6 has 280433 (91.2%) zeros Zeros
FLAG_DOCUMENT_7 has 307452 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_8 has 282487 (91.9%) zeros Zeros
FLAG_DOCUMENT_9 has 306313 (99.6%) zeros Zeros
FLAG_DOCUMENT_10 has 307504 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_11 has 306308 (99.6%) zeros Zeros
FLAG_DOCUMENT_12 has 307509 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_13 has 306427 (99.6%) zeros Zeros
FLAG_DOCUMENT_14 has 306608 (99.7%) zeros Zeros
FLAG_DOCUMENT_15 has 307139 (99.9%) zeros Zeros
FLAG_DOCUMENT_16 has 304458 (99.0%) zeros Zeros
FLAG_DOCUMENT_17 has 307429 (> 99.9%) zeros Zeros
FLAG_DOCUMENT_18 has 305011 (99.2%) zeros Zeros
FLAG_DOCUMENT_19 has 307328 (99.9%) zeros Zeros
FLAG_DOCUMENT_20 has 307355 (99.9%) zeros Zeros
FLAG_DOCUMENT_21 has 307408 (> 99.9%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_HOUR has 305885 (99.5%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_DAY has 306022 (99.5%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_WEEK has 298975 (97.2%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_MON has 263752 (85.8%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_QRT has 256936 (83.6%) zeros Zeros
AMT_REQ_CREDIT_BUREAU_YEAR has 71801 (23.3%) zeros Zeros

Reproduction

Analysis started2024-12-02 16:02:25.737402
Analysis finished2024-12-02 16:02:43.202988
Duration17.47 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

SK_ID_CURR
Real number (ℝ)

Unique 

Distinct307511
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278180.5186
Minimum100002
Maximum456255
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:43.777153image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum100002
5-th percentile117945.5
Q1189145.5
median278202
Q3367142.5
95-th percentile438427.5
Maximum456255
Range356253
Interquartile range (IQR)177997

Descriptive statistics

Standard deviation102790.1753
Coefficient of variation (CV)0.3695088926
Kurtosis-1.198987778
Mean278180.5186
Median Absolute Deviation (MAD)88999
Skewness-0.001200235077
Sum8.554356945 × 1010
Variance1.056582015 × 1010
MonotonicityStrictly increasing
2024-12-02T17:02:44.218930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100002 1
 
< 0.1%
337664 1
 
< 0.1%
337661 1
 
< 0.1%
337660 1
 
< 0.1%
337659 1
 
< 0.1%
337658 1
 
< 0.1%
337657 1
 
< 0.1%
337656 1
 
< 0.1%
337655 1
 
< 0.1%
337654 1
 
< 0.1%
Other values (307501) 307501
> 99.9%
ValueCountFrequency (%)
100002 1
< 0.1%
100003 1
< 0.1%
100004 1
< 0.1%
100006 1
< 0.1%
100007 1
< 0.1%
ValueCountFrequency (%)
456255 1
< 0.1%
456254 1
< 0.1%
456253 1
< 0.1%
456252 1
< 0.1%
456251 1
< 0.1%

TARGET
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08072881946
Minimum0
Maximum1
Zeros282686
Zeros (%)91.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:44.588625image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2724186456
Coefficient of variation (CV)3.37449064
Kurtosis7.475109389
Mean0.08072881946
Median Absolute Deviation (MAD)0
Skewness3.078158666
Sum24825
Variance0.0742119185
MonotonicityNot monotonic
2024-12-02T17:02:44.955150image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 282686
91.9%
1 24825
 
8.1%
ValueCountFrequency (%)
0 282686
91.9%
1 24825
 
8.1%
ValueCountFrequency (%)
1 24825
 
8.1%
0 282686
91.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:45.255540image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 278232
90.5%
1 29279
 
9.5%
2024-12-02T17:02:45.831362image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 278232
90.5%
1 29279
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 278232
90.5%
1 29279
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 278232
90.5%
1 29279
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 278232
90.5%
1 29279
 
9.5%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:46.030504image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row0
5th row1
ValueCountFrequency (%)
0 202448
65.8%
1 105059
34.2%
2 4
 
< 0.1%
2024-12-02T17:02:46.553488image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 202448
65.8%
1 105059
34.2%
2 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202448
65.8%
1 105059
34.2%
2 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 202448
65.8%
1 105059
34.2%
2 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 202448
65.8%
1 105059
34.2%
2 4
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:46.747154image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 202924
66.0%
1 104587
34.0%
2024-12-02T17:02:47.269889image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 202924
66.0%
1 104587
34.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 202924
66.0%
1 104587
34.0%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 202924
66.0%
1 104587
34.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 202924
66.0%
1 104587
34.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:47.462671image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 213312
69.4%
0 94199
30.6%
2024-12-02T17:02:47.968833image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 213312
69.4%
0 94199
30.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 213312
69.4%
0 94199
30.6%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 213312
69.4%
0 94199
30.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 213312
69.4%
0 94199
30.6%

CNT_CHILDREN
Real number (ℝ)

Zeros 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4170517477
Minimum0
Maximum19
Zeros215371
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:48.261037image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum19
Range19
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7221213844
Coefficient of variation (CV)1.731491088
Kurtosis7.904106359
Mean0.4170517477
Median Absolute Deviation (MAD)0
Skewness1.97460447
Sum128248
Variance0.5214592939
MonotonicityNot monotonic
2024-12-02T17:02:48.598142image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0 215371
70.0%
1 61119
 
19.9%
2 26749
 
8.7%
3 3717
 
1.2%
4 429
 
0.1%
5 84
 
< 0.1%
6 21
 
< 0.1%
7 7
 
< 0.1%
14 3
 
< 0.1%
8 2
 
< 0.1%
Other values (5) 9
 
< 0.1%
ValueCountFrequency (%)
0 215371
70.0%
1 61119
 
19.9%
2 26749
 
8.7%
3 3717
 
1.2%
4 429
 
0.1%
ValueCountFrequency (%)
19 2
< 0.1%
14 3
< 0.1%
12 2
< 0.1%
11 1
 
< 0.1%
10 2
< 0.1%

AMT_INCOME_TOTAL
Real number (ℝ)

Skewed 

Distinct2548
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168797.9193
Minimum25650
Maximum117000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:49.202645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum25650
5-th percentile67500
Q1112500
median147150
Q3202500
95-th percentile337500
Maximum117000000
Range116974350
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation237123.1463
Coefficient of variation (CV)1.404775291
Kurtosis191786.5544
Mean168797.9193
Median Absolute Deviation (MAD)43650
Skewness391.5596541
Sum5.190721696 × 1010
Variance5.62273865 × 1010
MonotonicityNot monotonic
2024-12-02T17:02:49.637369image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
135000 35750
 
11.6%
112500 31019
 
10.1%
157500 26556
 
8.6%
180000 24719
 
8.0%
90000 22483
 
7.3%
225000 20698
 
6.7%
202500 16341
 
5.3%
67500 11147
 
3.6%
270000 10827
 
3.5%
81000 6001
 
2.0%
Other values (2538) 101970
33.2%
ValueCountFrequency (%)
25650 2
 
< 0.1%
26100 3
 
< 0.1%
26460 1
 
< 0.1%
26550 2
 
< 0.1%
27000 66
< 0.1%
ValueCountFrequency (%)
117000000 1
< 0.1%
18000090 1
< 0.1%
13500000 1
< 0.1%
9000000 1
< 0.1%
6750000 1
< 0.1%

AMT_CREDIT
Real number (ℝ)

Distinct5603
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean599025.9997
Minimum45000
Maximum4050000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:50.071829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum45000
5-th percentile135000
Q1270000
median513531
Q3808650
95-th percentile1350000
Maximum4050000
Range4005000
Interquartile range (IQR)538650

Descriptive statistics

Standard deviation402490.777
Coefficient of variation (CV)0.6719086938
Kurtosis1.934041301
Mean599025.9997
Median Absolute Deviation (MAD)251469
Skewness1.234778497
Sum1.842070842 × 1011
Variance1.619988256 × 1011
MonotonicityNot monotonic
2024-12-02T17:02:50.578374image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450000 9709
 
3.2%
675000 8877
 
2.9%
225000 8162
 
2.7%
180000 7342
 
2.4%
270000 7241
 
2.4%
900000 6246
 
2.0%
254700 4500
 
1.5%
545040 4437
 
1.4%
808650 4152
 
1.4%
135000 3660
 
1.2%
Other values (5593) 243185
79.1%
ValueCountFrequency (%)
45000 230
0.1%
47970 218
0.1%
48519 1
 
< 0.1%
49455 19
 
< 0.1%
49500 40
 
< 0.1%
ValueCountFrequency (%)
4050000 8
< 0.1%
4031032.5 1
 
< 0.1%
4027680 1
 
< 0.1%
3956274 1
 
< 0.1%
3860019 1
 
< 0.1%

AMT_ANNUITY
Real number (ℝ)

Distinct13672
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27108.48784
Minimum1615.5
Maximum258025.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:51.057308image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1615.5
5-th percentile9000
Q116524
median24903
Q334596
95-th percentile53325
Maximum258025.5
Range256410
Interquartile range (IQR)18072

Descriptive statistics

Standard deviation14493.46107
Coefficient of variation (CV)0.5346466078
Kurtosis7.707755954
Mean27108.48784
Median Absolute Deviation (MAD)8811
Skewness1.579823725
Sum8336158204
Variance210060413.7
MonotonicityNot monotonic
2024-12-02T17:02:51.540875image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9000 6385
 
2.1%
13500 5514
 
1.8%
6750 2279
 
0.7%
10125 2035
 
0.7%
37800 1602
 
0.5%
11250 1459
 
0.5%
26217 1453
 
0.5%
20250 1345
 
0.4%
12375 1339
 
0.4%
31653 1269
 
0.4%
Other values (13662) 282831
92.0%
ValueCountFrequency (%)
1615.5 1
< 0.1%
1980 2
< 0.1%
1993.5 1
< 0.1%
2052 1
< 0.1%
2164.5 2
< 0.1%
ValueCountFrequency (%)
258025.5 1
 
< 0.1%
230161.5 1
 
< 0.1%
225000 23
< 0.1%
220297.5 1
 
< 0.1%
216589.5 1
 
< 0.1%

AMT_GOODS_PRICE
Real number (ℝ)

Distinct1002
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean538316.2944
Minimum40500
Maximum4050000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:52.009570image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum40500
5-th percentile135000
Q1238500
median450000
Q3679500
95-th percentile1305000
Maximum4050000
Range4009500
Interquartile range (IQR)441000

Descriptive statistics

Standard deviation369288.9822
Coefficient of variation (CV)0.6860074386
Kurtosis2.437440173
Mean538316.2944
Median Absolute Deviation (MAD)225000
Skewness1.35014255
Sum1.65538182 × 1011
Variance1.363743524 × 1011
MonotonicityNot monotonic
2024-12-02T17:02:52.574196image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
450000 26300
 
8.6%
225000 25282
 
8.2%
675000 24962
 
8.1%
900000 15416
 
5.0%
270000 11428
 
3.7%
180000 10123
 
3.3%
454500 9157
 
3.0%
1125000 9050
 
2.9%
135000 8206
 
2.7%
315000 5225
 
1.7%
Other values (992) 162362
52.8%
ValueCountFrequency (%)
40500 1
 
< 0.1%
45000 1169
0.4%
49500 157
 
0.1%
50751 1
 
< 0.1%
54000 290
 
0.1%
ValueCountFrequency (%)
4050000 8
< 0.1%
3825000 1
 
< 0.1%
3712500 1
 
< 0.1%
3600000 3
 
< 0.1%
3555000 1
 
< 0.1%
Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:52.880117image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row2
3rd row7
4th row7
5th row7
ValueCountFrequency (%)
7 248526
80.8%
2 40149
 
13.1%
6 11370
 
3.7%
1 3267
 
1.1%
5 1770
 
0.6%
0 1292
 
0.4%
4 866
 
0.3%
3 271
 
0.1%
2024-12-02T17:02:53.514969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 248526
80.8%
2 40149
 
13.1%
6 11370
 
3.7%
1 3267
 
1.1%
5 1770
 
0.6%
0 1292
 
0.4%
4 866
 
0.3%
3 271
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 248526
80.8%
2 40149
 
13.1%
6 11370
 
3.7%
1 3267
 
1.1%
5 1770
 
0.6%
0 1292
 
0.4%
4 866
 
0.3%
3 271
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 248526
80.8%
2 40149
 
13.1%
6 11370
 
3.7%
1 3267
 
1.1%
5 1770
 
0.6%
0 1292
 
0.4%
4 866
 
0.3%
3 271
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 248526
80.8%
2 40149
 
13.1%
6 11370
 
3.7%
1 3267
 
1.1%
5 1770
 
0.6%
0 1292
 
0.4%
4 866
 
0.3%
3 271
 
0.1%
Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:53.741092image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row4
3rd row7
4th row7
5th row7
ValueCountFrequency (%)
7 158774
51.6%
1 71617
23.3%
3 55362
 
18.0%
4 21703
 
7.1%
6 22
 
< 0.1%
5 18
 
< 0.1%
0 10
 
< 0.1%
2 5
 
< 0.1%
2024-12-02T17:02:54.279727image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 158774
51.6%
1 71617
23.3%
3 55362
 
18.0%
4 21703
 
7.1%
6 22
 
< 0.1%
5 18
 
< 0.1%
0 10
 
< 0.1%
2 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 158774
51.6%
1 71617
23.3%
3 55362
 
18.0%
4 21703
 
7.1%
6 22
 
< 0.1%
5 18
 
< 0.1%
0 10
 
< 0.1%
2 5
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 158774
51.6%
1 71617
23.3%
3 55362
 
18.0%
4 21703
 
7.1%
6 22
 
< 0.1%
5 18
 
< 0.1%
0 10
 
< 0.1%
2 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 158774
51.6%
1 71617
23.3%
3 55362
 
18.0%
4 21703
 
7.1%
6 22
 
< 0.1%
5 18
 
< 0.1%
0 10
 
< 0.1%
2 5
 
< 0.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:54.498394image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row4
4th row4
5th row4
ValueCountFrequency (%)
4 218391
71.0%
1 74863
 
24.3%
2 10277
 
3.3%
3 3816
 
1.2%
0 164
 
0.1%
2024-12-02T17:02:55.028295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 218391
71.0%
1 74863
 
24.3%
2 10277
 
3.3%
3 3816
 
1.2%
0 164
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 218391
71.0%
1 74863
 
24.3%
2 10277
 
3.3%
3 3816
 
1.2%
0 164
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 218391
71.0%
1 74863
 
24.3%
2 10277
 
3.3%
3 3816
 
1.2%
0 164
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 218391
71.0%
1 74863
 
24.3%
2 10277
 
3.3%
3 3816
 
1.2%
0 164
 
0.1%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:55.228736image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row0
5th row3
ValueCountFrequency (%)
1 196432
63.9%
3 45444
 
14.8%
0 29775
 
9.7%
2 19770
 
6.4%
5 16088
 
5.2%
4 2
 
< 0.1%
2024-12-02T17:02:55.766495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 196432
63.9%
3 45444
 
14.8%
0 29775
 
9.7%
2 19770
 
6.4%
5 16088
 
5.2%
4 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 196432
63.9%
3 45444
 
14.8%
0 29775
 
9.7%
2 19770
 
6.4%
5 16088
 
5.2%
4 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 196432
63.9%
3 45444
 
14.8%
0 29775
 
9.7%
2 19770
 
6.4%
5 16088
 
5.2%
4 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 196432
63.9%
3 45444
 
14.8%
0 29775
 
9.7%
2 19770
 
6.4%
5 16088
 
5.2%
4 2
 
< 0.1%
Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:55.969805image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 272868
88.7%
5 14840
 
4.8%
2 11183
 
3.6%
4 4881
 
1.6%
3 2617
 
0.9%
0 1122
 
0.4%
2024-12-02T17:02:56.503021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 272868
88.7%
5 14840
 
4.8%
2 11183
 
3.6%
4 4881
 
1.6%
3 2617
 
0.9%
0 1122
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 272868
88.7%
5 14840
 
4.8%
2 11183
 
3.6%
4 4881
 
1.6%
3 2617
 
0.9%
0 1122
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 272868
88.7%
5 14840
 
4.8%
2 11183
 
3.6%
4 4881
 
1.6%
3 2617
 
0.9%
0 1122
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 272868
88.7%
5 14840
 
4.8%
2 11183
 
3.6%
4 4881
 
1.6%
3 2617
 
0.9%
0 1122
 
0.4%
Distinct81
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02086811206
Minimum0.00029
Maximum0.072508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:02:56.862692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.00029
5-th percentile0.00496
Q10.010006
median0.01885
Q30.028663
95-th percentile0.04622
Maximum0.072508
Range0.072218
Interquartile range (IQR)0.018657

Descriptive statistics

Standard deviation0.01383128012
Coefficient of variation (CV)0.66279499
Kurtosis3.260065334
Mean0.02086811206
Median Absolute Deviation (MAD)0.009193
Skewness1.488008521
Sum6417.174007
Variance0.0001913043098
MonotonicityNot monotonic
2024-12-02T17:02:57.279054image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.035792 16408
 
5.3%
0.04622 13442
 
4.4%
0.030755 12163
 
4.0%
0.025164 11950
 
3.9%
0.026392 11601
 
3.8%
0.031329 11321
 
3.7%
0.028663 11157
 
3.6%
0.019101 8694
 
2.8%
0.072508 8412
 
2.7%
0.020713 8066
 
2.6%
Other values (71) 194297
63.2%
ValueCountFrequency (%)
0.00029 2
 
< 0.1%
0.000533 39
 
< 0.1%
0.000938 28
 
< 0.1%
0.001276 558
0.2%
0.001333 235
0.1%
ValueCountFrequency (%)
0.072508 8412
2.7%
0.04622 13442
4.4%
0.035792 16408
5.3%
0.032561 6636
2.2%
0.031329 11321
3.7%

DAYS_BIRTH
Real number (ℝ)

Distinct17460
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-16036.99507
Minimum-25229
Maximum-7489
Zeros0
Zeros (%)0.0%
Negative307511
Negative (%)100.0%
Memory size2.3 MiB
2024-12-02T17:02:57.747582image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-25229
5-th percentile-23204
Q1-19682
median-15750
Q3-12413
95-th percentile-9407
Maximum-7489
Range17740
Interquartile range (IQR)7269

Descriptive statistics

Standard deviation4363.988632
Coefficient of variation (CV)-0.2721200957
Kurtosis-1.04912577
Mean-16036.99507
Median Absolute Deviation (MAD)3630
Skewness-0.1156733117
Sum-4931552390
Variance19044396.78
MonotonicityNot monotonic
2024-12-02T17:02:58.171015image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-13749 43
 
< 0.1%
-13481 42
 
< 0.1%
-18248 41
 
< 0.1%
-10020 41
 
< 0.1%
-15771 40
 
< 0.1%
-10292 40
 
< 0.1%
-14267 39
 
< 0.1%
-13263 39
 
< 0.1%
-11664 39
 
< 0.1%
-14395 39
 
< 0.1%
Other values (17450) 307108
99.9%
ValueCountFrequency (%)
-25229 1
 
< 0.1%
-25201 2
< 0.1%
-25200 1
 
< 0.1%
-25197 2
< 0.1%
-25196 4
< 0.1%
ValueCountFrequency (%)
-7489 1
 
< 0.1%
-7673 1
 
< 0.1%
-7676 2
< 0.1%
-7678 3
< 0.1%
-7679 1
 
< 0.1%

DAYS_EMPLOYED
Real number (ℝ)

Distinct12574
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63815.0459
Minimum-17912
Maximum365243
Zeros2
Zeros (%)< 0.1%
Negative252135
Negative (%)82.0%
Memory size2.3 MiB
2024-12-02T17:02:58.587005image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-17912
5-th percentile-6742.5
Q1-2760
median-1213
Q3-289
95-th percentile365243
Maximum365243
Range383155
Interquartile range (IQR)2471

Descriptive statistics

Standard deviation141275.7665
Coefficient of variation (CV)2.213831621
Kurtosis0.7716123807
Mean63815.0459
Median Absolute Deviation (MAD)1091
Skewness1.664346198
Sum1.962382858 × 1010
Variance1.995884221 × 1010
MonotonicityNot monotonic
2024-12-02T17:02:59.004387image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
365243 55374
 
18.0%
-200 156
 
0.1%
-224 152
 
< 0.1%
-230 151
 
< 0.1%
-199 151
 
< 0.1%
-212 150
 
< 0.1%
-384 143
 
< 0.1%
-229 143
 
< 0.1%
-231 140
 
< 0.1%
-215 138
 
< 0.1%
Other values (12564) 250813
81.6%
ValueCountFrequency (%)
-17912 1
< 0.1%
-17583 1
< 0.1%
-17546 1
< 0.1%
-17531 1
< 0.1%
-17522 1
< 0.1%
ValueCountFrequency (%)
365243 55374
18.0%
0 2
 
< 0.1%
-1 1
 
< 0.1%
-2 2
 
< 0.1%
-3 3
 
< 0.1%

DAYS_REGISTRATION
Real number (ℝ)

Distinct15688
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4986.120328
Minimum-24672
Maximum0
Zeros80
Zeros (%)< 0.1%
Negative307431
Negative (%)> 99.9%
Memory size2.3 MiB
2024-12-02T17:02:59.422070image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-24672
5-th percentile-11416
Q1-7479.5
median-4504
Q3-2010
95-th percentile-330
Maximum0
Range24672
Interquartile range (IQR)5469.5

Descriptive statistics

Standard deviation3522.886321
Coefficient of variation (CV)-0.706538569
Kurtosis-0.3213466019
Mean-4986.120328
Median Absolute Deviation (MAD)2699
Skewness-0.5908716157
Sum-1533286848
Variance12410728.03
MonotonicityNot monotonic
2024-12-02T17:02:59.850372image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 113
 
< 0.1%
-7 98
 
< 0.1%
-6 96
 
< 0.1%
-4 92
 
< 0.1%
-2 92
 
< 0.1%
-5 86
 
< 0.1%
-3 84
 
< 0.1%
-9 84
 
< 0.1%
-14 80
 
< 0.1%
-21 80
 
< 0.1%
Other values (15678) 306606
99.7%
ValueCountFrequency (%)
-24672 1
< 0.1%
-23738 1
< 0.1%
-23416 1
< 0.1%
-22928 1
< 0.1%
-22858 1
< 0.1%
ValueCountFrequency (%)
0 80
< 0.1%
-1 113
< 0.1%
-2 92
< 0.1%
-3 84
< 0.1%
-4 92
< 0.1%

DAYS_ID_PUBLISH
Real number (ℝ)

Distinct6168
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2994.202373
Minimum-7197
Maximum0
Zeros16
Zeros (%)< 0.1%
Negative307495
Negative (%)> 99.9%
Memory size2.3 MiB
2024-12-02T17:03:00.255673image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-7197
5-th percentile-4944
Q1-4299
median-3254
Q3-1720
95-th percentile-375
Maximum0
Range7197
Interquartile range (IQR)2579

Descriptive statistics

Standard deviation1509.450419
Coefficient of variation (CV)-0.5041243813
Kurtosis-1.106807894
Mean-2994.202373
Median Absolute Deviation (MAD)1186
Skewness0.3493274932
Sum-920750166
Variance2278440.567
MonotonicityNot monotonic
2024-12-02T17:03:00.703391image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4053 169
 
0.1%
-4095 162
 
0.1%
-4046 161
 
0.1%
-4417 159
 
0.1%
-4256 158
 
0.1%
-4032 157
 
0.1%
-4151 157
 
0.1%
-4200 156
 
0.1%
-4171 155
 
0.1%
-4214 155
 
0.1%
Other values (6158) 305922
99.5%
ValueCountFrequency (%)
-7197 1
< 0.1%
-6551 1
< 0.1%
-6383 1
< 0.1%
-6337 1
< 0.1%
-6274 1
< 0.1%
ValueCountFrequency (%)
0 16
 
< 0.1%
-1 64
< 0.1%
-2 50
< 0.1%
-3 51
< 0.1%
-4 57
< 0.1%

OWN_CAR_AGE
Real number (ℝ)

Distinct62
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.04105219
Minimum0
Maximum91
Zeros2134
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:01.118197image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q19
median9
Q39
95-th percentile19
Maximum91
Range91
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.115228485
Coefficient of variation (CV)0.7086138336
Kurtosis35.47644755
Mean10.04105219
Median Absolute Deviation (MAD)0
Skewness5.239470755
Sum3087734
Variance50.6264764
MonotonicityNot monotonic
2024-12-02T17:03:01.511461image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 207949
67.6%
7 7424
 
2.4%
6 6382
 
2.1%
3 6370
 
2.1%
8 5887
 
1.9%
2 5852
 
1.9%
4 5557
 
1.8%
1 5280
 
1.7%
10 4806
 
1.6%
14 4594
 
1.5%
Other values (52) 47410
 
15.4%
ValueCountFrequency (%)
0 2134
 
0.7%
1 5280
1.7%
2 5852
1.9%
3 6370
2.1%
4 5557
1.8%
ValueCountFrequency (%)
91 2
 
< 0.1%
69 1
 
< 0.1%
65 891
 
0.3%
64 2443
0.8%
63 2
 
< 0.1%

FLAG_MOBIL
Real number (ℝ)

Skewed 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9999967481
Minimum0
Maximum1
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:01.819882image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.001803307015
Coefficient of variation (CV)0.00180331288
Kurtosis307511
Mean0.9999967481
Median Absolute Deviation (MAD)0
Skewness-554.5367436
Sum307510
Variance3.251916192 × 10-6
MonotonicityNot monotonic
2024-12-02T17:03:02.145503image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 307510
> 99.9%
0 1
 
< 0.1%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 307510
> 99.9%
ValueCountFrequency (%)
1 307510
> 99.9%
0 1
 
< 0.1%

FLAG_EMP_PHONE
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8198893698
Minimum0
Maximum1
Zeros55386
Zeros (%)18.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:02.447394image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3842801989
Coefficient of variation (CV)0.4686976232
Kurtosis0.7718519499
Mean0.8198893698
Median Absolute Deviation (MAD)0
Skewness-1.664886462
Sum252125
Variance0.1476712713
MonotonicityNot monotonic
2024-12-02T17:03:02.746439image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 252125
82.0%
0 55386
 
18.0%
ValueCountFrequency (%)
0 55386
 
18.0%
1 252125
82.0%
ValueCountFrequency (%)
1 252125
82.0%
0 55386
 
18.0%

FLAG_WORK_PHONE
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1993684779
Minimum0
Maximum1
Zeros246203
Zeros (%)80.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:03.039624image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3995262282
Coefficient of variation (CV)2.003958863
Kurtosis0.2648759067
Mean0.1993684779
Median Absolute Deviation (MAD)0
Skewness1.504949894
Sum61308
Variance0.159621207
MonotonicityNot monotonic
2024-12-02T17:03:03.336867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 246203
80.1%
1 61308
 
19.9%
ValueCountFrequency (%)
0 246203
80.1%
1 61308
 
19.9%
ValueCountFrequency (%)
1 61308
 
19.9%
0 246203
80.1%

FLAG_CONT_MOBILE
Real number (ℝ)

Skewed 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9981334001
Minimum0
Maximum1
Zeros574
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:03.628367image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04316389414
Coefficient of variation (CV)0.04324461454
Kurtosis530.7439687
Mean0.9981334001
Median Absolute Deviation (MAD)0
Skewness-23.08117235
Sum306937
Variance0.001863121758
MonotonicityNot monotonic
2024-12-02T17:03:03.932476image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 306937
99.8%
0 574
 
0.2%
ValueCountFrequency (%)
0 574
 
0.2%
1 306937
99.8%
ValueCountFrequency (%)
1 306937
99.8%
0 574
 
0.2%

FLAG_PHONE
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2810663684
Minimum0
Maximum1
Zeros221080
Zeros (%)71.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:04.220217image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4495205469
Coefficient of variation (CV)1.599339506
Kurtosis-1.051170063
Mean0.2810663684
Median Absolute Deviation (MAD)0
Skewness0.974082529
Sum86431
Variance0.202068722
MonotonicityNot monotonic
2024-12-02T17:03:04.544575image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 221080
71.9%
1 86431
 
28.1%
ValueCountFrequency (%)
0 221080
71.9%
1 86431
 
28.1%
ValueCountFrequency (%)
1 86431
 
28.1%
0 221080
71.9%

FLAG_EMAIL
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05671992221
Minimum0
Maximum1
Zeros290069
Zeros (%)94.3%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:04.837361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2313070397
Coefficient of variation (CV)4.078056364
Kurtosis12.690846
Mean0.05671992221
Median Absolute Deviation (MAD)0
Skewness3.832853175
Sum17442
Variance0.05350294663
MonotonicityNot monotonic
2024-12-02T17:03:05.143533image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 290069
94.3%
1 17442
 
5.7%
ValueCountFrequency (%)
0 290069
94.3%
1 17442
 
5.7%
ValueCountFrequency (%)
1 17442
 
5.7%
0 290069
94.3%
Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:05.844705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.250007317
Min length1

Characters and Unicode

Total characters384391
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9
2nd row4
3rd row9
4th row9
5th row4
ValueCountFrequency (%)
0 96391
31.3%
9 55186
17.9%
15 32102
 
10.4%
4 27570
 
9.0%
11 21371
 
6.9%
5 18603
 
6.0%
7 11380
 
3.7%
1 9813
 
3.2%
12 8537
 
2.8%
17 6721
 
2.2%
Other values (9) 19837
 
6.5%
2024-12-02T17:03:06.527824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 108064
28.1%
0 98484
25.6%
9 55186
14.4%
5 50705
13.2%
4 28321
 
7.4%
7 18101
 
4.7%
2 13190
 
3.4%
3 8598
 
2.2%
8 1874
 
0.5%
6 1868
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 384391
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 108064
28.1%
0 98484
25.6%
9 55186
14.4%
5 50705
13.2%
4 28321
 
7.4%
7 18101
 
4.7%
2 13190
 
3.4%
3 8598
 
2.2%
8 1874
 
0.5%
6 1868
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 384391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 108064
28.1%
0 98484
25.6%
9 55186
14.4%
5 50705
13.2%
4 28321
 
7.4%
7 18101
 
4.7%
2 13190
 
3.4%
3 8598
 
2.2%
8 1874
 
0.5%
6 1868
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 108064
28.1%
0 98484
25.6%
9 55186
14.4%
5 50705
13.2%
4 28321
 
7.4%
7 18101
 
4.7%
2 13190
 
3.4%
3 8598
 
2.2%
8 1874
 
0.5%
6 1868
 
0.5%

CNT_FAM_MEMBERS
Real number (ℝ)

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.152664458
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:06.850803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum20
Range19
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9106786909
Coefficient of variation (CV)0.4230472091
Kurtosis2.802016907
Mean2.152664458
Median Absolute Deviation (MAD)0
Skewness0.9875489946
Sum661968
Variance0.8293356781
MonotonicityNot monotonic
2024-12-02T17:03:07.201579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 158359
51.5%
1 67847
22.1%
3 52601
 
17.1%
4 24697
 
8.0%
5 3478
 
1.1%
6 408
 
0.1%
7 81
 
< 0.1%
8 20
 
< 0.1%
9 6
 
< 0.1%
10 3
 
< 0.1%
Other values (7) 11
 
< 0.1%
ValueCountFrequency (%)
1 67847
22.1%
2 158359
51.5%
3 52601
 
17.1%
4 24697
 
8.0%
5 3478
 
1.1%
ValueCountFrequency (%)
20 2
< 0.1%
16 2
< 0.1%
15 1
< 0.1%
14 2
< 0.1%
13 1
< 0.1%

REGION_RATING_CLIENT
Real number (ℝ)

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.052463164
Minimum1
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:07.540170image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum3
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5090339028
Coefficient of variation (CV)0.2480112246
Kurtosis0.8004164375
Mean2.052463164
Median Absolute Deviation (MAD)0
Skewness0.08746834971
Sum631155
Variance0.2591155142
MonotonicityNot monotonic
2024-12-02T17:03:07.884734image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
2 226984
73.8%
3 48330
 
15.7%
1 32197
 
10.5%
ValueCountFrequency (%)
1 32197
 
10.5%
2 226984
73.8%
3 48330
 
15.7%
ValueCountFrequency (%)
3 48330
 
15.7%
2 226984
73.8%
1 32197
 
10.5%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.031520824
Minimum1
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:08.222847image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile3
Maximum3
Range2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5027370329
Coefficient of variation (CV)0.2474683139
Kurtosis0.9335838303
Mean2.031520824
Median Absolute Deviation (MAD)0
Skewness0.05972981215
Sum624715
Variance0.2527445243
MonotonicityNot monotonic
2024-12-02T17:03:08.555694image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
2 229484
74.6%
3 43860
 
14.3%
1 34167
 
11.1%
ValueCountFrequency (%)
1 34167
 
11.1%
2 229484
74.6%
3 43860
 
14.3%
ValueCountFrequency (%)
3 43860
 
14.3%
2 229484
74.6%
1 34167
 
11.1%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:08.892777image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row1
3rd row1
4th row6
5th row4
ValueCountFrequency (%)
5 53901
17.5%
6 51934
16.9%
1 50714
16.5%
4 50591
16.5%
0 50338
16.4%
2 33852
11.0%
3 16181
 
5.3%
2024-12-02T17:03:09.527160image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 53901
17.5%
6 51934
16.9%
1 50714
16.5%
4 50591
16.5%
0 50338
16.4%
2 33852
11.0%
3 16181
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 53901
17.5%
6 51934
16.9%
1 50714
16.5%
4 50591
16.5%
0 50338
16.4%
2 33852
11.0%
3 16181
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 53901
17.5%
6 51934
16.9%
1 50714
16.5%
4 50591
16.5%
0 50338
16.4%
2 33852
11.0%
3 16181
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 53901
17.5%
6 51934
16.9%
1 50714
16.5%
4 50591
16.5%
0 50338
16.4%
2 33852
11.0%
3 16181
 
5.3%

HOUR_APPR_PROCESS_START
Real number (ℝ)

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.06341887
Minimum0
Maximum23
Zeros40
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:09.836458image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q110
median12
Q314
95-th percentile17
Maximum23
Range23
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.265832255
Coefficient of variation (CV)0.270721948
Kurtosis-0.1941728655
Mean12.06341887
Median Absolute Deviation (MAD)2
Skewness-0.02802445946
Sum3709634
Variance10.66566032
MonotonicityNot monotonic
2024-12-02T17:03:10.187440image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10 37722
12.3%
11 37229
12.1%
12 34233
11.1%
13 30959
10.1%
14 27682
9.0%
9 27384
8.9%
15 24839
8.1%
16 20385
6.6%
8 15127
4.9%
17 14900
 
4.8%
Other values (14) 37051
12.0%
ValueCountFrequency (%)
0 40
 
< 0.1%
1 86
 
< 0.1%
2 305
 
0.1%
3 1230
0.4%
4 2090
0.7%
ValueCountFrequency (%)
23 41
 
< 0.1%
22 150
 
< 0.1%
21 405
 
0.1%
20 1196
 
0.4%
19 3848
1.3%

REG_REGION_NOT_LIVE_REGION
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0151441737
Minimum0
Maximum1
Zeros302854
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:10.495939image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1221264763
Coefficient of variation (CV)8.064254852
Kurtosis61.04838402
Mean0.0151441737
Median Absolute Deviation (MAD)0
Skewness7.940276253
Sum4657
Variance0.01491487621
MonotonicityNot monotonic
2024-12-02T17:03:10.803080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 302854
98.5%
1 4657
 
1.5%
ValueCountFrequency (%)
0 302854
98.5%
1 4657
 
1.5%
ValueCountFrequency (%)
1 4657
 
1.5%
0 302854
98.5%

REG_REGION_NOT_WORK_REGION
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05076891558
Minimum0
Maximum1
Zeros291899
Zeros (%)94.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:11.126893image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2195258288
Coefficient of variation (CV)4.324020442
Kurtosis14.75083559
Mean0.05076891558
Median Absolute Deviation (MAD)0
Skewness4.092766748
Sum15612
Variance0.04819158951
MonotonicityNot monotonic
2024-12-02T17:03:11.428259image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 291899
94.9%
1 15612
 
5.1%
ValueCountFrequency (%)
0 291899
94.9%
1 15612
 
5.1%
ValueCountFrequency (%)
1 15612
 
5.1%
0 291899
94.9%

LIVE_REGION_NOT_WORK_REGION
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04065870814
Minimum0
Maximum1
Zeros295008
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:11.729082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1974986188
Coefficient of variation (CV)4.857474028
Kurtosis19.63769792
Mean0.04065870814
Median Absolute Deviation (MAD)0
Skewness4.651620169
Sum12503
Variance0.03900570444
MonotonicityNot monotonic
2024-12-02T17:03:12.036823image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 295008
95.9%
1 12503
 
4.1%
ValueCountFrequency (%)
0 295008
95.9%
1 12503
 
4.1%
ValueCountFrequency (%)
1 12503
 
4.1%
0 295008
95.9%

REG_CITY_NOT_LIVE_CITY
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07817281333
Minimum0
Maximum1
Zeros283472
Zeros (%)92.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:12.328685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2684437724
Coefficient of variation (CV)3.433978655
Kurtosis7.877120671
Mean0.07817281333
Median Absolute Deviation (MAD)0
Skewness3.142780527
Sum24039
Variance0.07206205893
MonotonicityNot monotonic
2024-12-02T17:03:12.639068image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 283472
92.2%
1 24039
 
7.8%
ValueCountFrequency (%)
0 283472
92.2%
1 24039
 
7.8%
ValueCountFrequency (%)
1 24039
 
7.8%
0 283472
92.2%

REG_CITY_NOT_WORK_CITY
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2304535448
Minimum0
Maximum1
Zeros236644
Zeros (%)77.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:12.932176image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4211238359
Coefficient of variation (CV)1.827369748
Kurtosis-0.3612503173
Mean0.2304535448
Median Absolute Deviation (MAD)0
Skewness1.280137505
Sum70867
Variance0.1773452852
MonotonicityNot monotonic
2024-12-02T17:03:13.228213image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 236644
77.0%
1 70867
 
23.0%
ValueCountFrequency (%)
0 236644
77.0%
1 70867
 
23.0%
ValueCountFrequency (%)
1 70867
 
23.0%
0 236644
77.0%

LIVE_CITY_NOT_WORK_CITY
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1795545525
Minimum0
Maximum1
Zeros252296
Zeros (%)82.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:13.511647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3838166154
Coefficient of variation (CV)2.137604477
Kurtosis0.7882204506
Mean0.1795545525
Median Absolute Deviation (MAD)0
Skewness1.669794995
Sum55215
Variance0.1473151942
MonotonicityNot monotonic
2024-12-02T17:03:13.812104image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 252296
82.0%
1 55215
 
18.0%
ValueCountFrequency (%)
0 252296
82.0%
1 55215
 
18.0%
ValueCountFrequency (%)
1 55215
 
18.0%
0 252296
82.0%
Distinct58
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:14.320493image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.680567524
Min length1

Characters and Unicode

Total characters516793
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row39
3rd row11
4th row5
5th row37
ValueCountFrequency (%)
5 67992
22.1%
57 55374
18.0%
42 38412
12.5%
33 16683
 
5.4%
30 11193
 
3.6%
4 10553
 
3.4%
11 10404
 
3.4%
39 8893
 
2.9%
51 7831
 
2.5%
28 6880
 
2.2%
Other values (48) 73296
23.8%
2024-12-02T17:03:15.137888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 150181
29.1%
3 76026
14.7%
4 68642
13.3%
7 66638
12.9%
2 60349
11.7%
1 45808
 
8.9%
0 19338
 
3.7%
9 10655
 
2.1%
6 9955
 
1.9%
8 9201
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 516793
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 150181
29.1%
3 76026
14.7%
4 68642
13.3%
7 66638
12.9%
2 60349
11.7%
1 45808
 
8.9%
0 19338
 
3.7%
9 10655
 
2.1%
6 9955
 
1.9%
8 9201
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 516793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 150181
29.1%
3 76026
14.7%
4 68642
13.3%
7 66638
12.9%
2 60349
11.7%
1 45808
 
8.9%
0 19338
 
3.7%
9 10655
 
2.1%
6 9955
 
1.9%
8 9201
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 516793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 150181
29.1%
3 76026
14.7%
4 68642
13.3%
7 66638
12.9%
2 60349
11.7%
1 45808
 
8.9%
0 19338
 
3.7%
9 10655
 
2.1%
6 9955
 
1.9%
8 9201
 
1.8%

EXT_SOURCE_1
Real number (ℝ)

Distinct114584
Distinct (%)37.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5043106959
Minimum0.01456813241
Maximum0.9626927706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:15.530226image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.01456813241
5-th percentile0.2259629465
Q10.5059979305
median0.5059979305
Q30.5059979305
95-th percentile0.7742504188
Maximum0.9626927706
Range0.9481246381
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1394081803
Coefficient of variation (CV)0.2764331223
Kurtosis1.671290746
Mean0.5043106959
Median Absolute Deviation (MAD)0
Skewness-0.1509975658
Sum155081.0864
Variance0.01943464073
MonotonicityNot monotonic
2024-12-02T17:03:15.969155image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5059979305 173380
56.4%
0.6051516612 5
 
< 0.1%
0.6227066347 5
 
< 0.1%
0.7657236984 5
 
< 0.1%
0.5810147956 5
 
< 0.1%
0.52819743 5
 
< 0.1%
0.4990017461 5
 
< 0.1%
0.5464264086 5
 
< 0.1%
0.3563226644 5
 
< 0.1%
0.443982118 5
 
< 0.1%
Other values (114574) 134086
43.6%
ValueCountFrequency (%)
0.01456813241 1
< 0.1%
0.0146914824 1
< 0.1%
0.0150529213 1
< 0.1%
0.01560008058 1
< 0.1%
0.01709465779 1
< 0.1%
ValueCountFrequency (%)
0.9626927706 1
< 0.1%
0.9516239622 1
< 0.1%
0.9476493854 1
< 0.1%
0.9460976144 1
< 0.1%
0.9460755215 1
< 0.1%

EXT_SOURCE_2
Real number (ℝ)

Distinct119831
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5145033543
Minimum8.173616519 × 10-8
Maximum0.8549996664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:16.386112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.173616519 × 10-8
5-th percentile0.1336355121
Q10.392973721
median0.5659614261
Q30.6634218023
95-th percentile0.7476805156
Maximum0.8549996664
Range0.8549995847
Interquartile range (IQR)0.2704480813

Descriptive statistics

Standard deviation0.1908699315
Coefficient of variation (CV)0.3709789838
Kurtosis-0.2622570346
Mean0.5145033543
Median Absolute Deviation (MAD)0.1187905139
Skewness-0.7959400363
Sum158215.441
Variance0.03643133077
MonotonicityNot monotonic
2024-12-02T17:03:16.793459image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2858978721 721
 
0.2%
0.5659614261 662
 
0.2%
0.2622583692 417
 
0.1%
0.2652563402 343
 
0.1%
0.1596792335 322
 
0.1%
0.2653117485 306
 
0.1%
0.2665197754 244
 
0.1%
0.263143591 243
 
0.1%
0.1621445677 238
 
0.1%
0.162192106 234
 
0.1%
Other values (119821) 303781
98.8%
ValueCountFrequency (%)
8.173616519 × 10-81
< 0.1%
1.315955581 × 10-61
< 0.1%
5.002108762 × 10-61
< 0.1%
5.600337749 × 10-61
< 0.1%
5.939650929 × 10-61
< 0.1%
ValueCountFrequency (%)
0.8549996664 26
< 0.1%
0.8217142128 1
 
< 0.1%
0.8213936274 1
 
< 0.1%
0.8206159442 1
 
< 0.1%
0.8206095061 1
 
< 0.1%

EXT_SOURCE_3
Real number (ℝ)

Distinct814
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5156949092
Minimum0.0005272652387
Maximum0.8960095495
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:17.210463image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.0005272652387
5-th percentile0.1745642656
Q10.4170996683
median0.5352762505
Q30.6363761711
95-th percentile0.7776594426
Maximum0.8960095495
Range0.8954822843
Interquartile range (IQR)0.2192765028

Descriptive statistics

Standard deviation0.1747357171
Coefficient of variation (CV)0.338835451
Kurtosis-0.04869212166
Mean0.5156949092
Median Absolute Deviation (MAD)0.1077493136
Skewness-0.5376966969
Sum158581.8572
Variance0.03053257083
MonotonicityNot monotonic
2024-12-02T17:03:17.627705image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5352762505 61751
 
20.1%
0.7463002131 1460
 
0.5%
0.7136313997 1315
 
0.4%
0.6940926425 1276
 
0.4%
0.6706517531 1191
 
0.4%
0.652896552 1154
 
0.4%
0.5814837058 1141
 
0.4%
0.6894791426 1138
 
0.4%
0.5954562029 1136
 
0.4%
0.5549467685 1132
 
0.4%
Other values (804) 234817
76.4%
ValueCountFrequency (%)
0.0005272652387 886
0.3%
0.01134571943 1
 
< 0.1%
0.01271592386 1
 
< 0.1%
0.01394846558 1
 
< 0.1%
0.01414826552 1
 
< 0.1%
ValueCountFrequency (%)
0.8960095495 1
 
< 0.1%
0.8939760746 2
 
< 0.1%
0.8876642018 1
 
< 0.1%
0.8854883942 3
 
< 0.1%
0.8825303128 26
< 0.1%

APARTMENTS_AVG
Real number (ℝ)

Distinct2339
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1022965266
Minimum0
Maximum1
Zeros751
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:18.036544image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0165
Q10.0876
median0.0876
Q30.0876
95-th percentile0.2392
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07741245073
Coefficient of variation (CV)0.7567456421
Kurtosis27.1004936
Mean0.1022965266
Median Absolute Deviation (MAD)0
Skewness4.121980685
Sum31457.3072
Variance0.005992687527
MonotonicityNot monotonic
2024-12-02T17:03:18.469125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0876 156580
50.9%
0.0825 6663
 
2.2%
0.0619 6332
 
2.1%
0.0928 4404
 
1.4%
0.0722 3986
 
1.3%
0.0082 3507
 
1.1%
0.0165 3027
 
1.0%
0.1031 2892
 
0.9%
0.1485 2769
 
0.9%
0.0124 2721
 
0.9%
Other values (2329) 114630
37.3%
ValueCountFrequency (%)
0 751
0.2%
0.001 197
 
0.1%
0.0014 1
 
< 0.1%
0.0015 6
 
< 0.1%
0.0017 1
 
< 0.1%
ValueCountFrequency (%)
1 147
< 0.1%
0.9907 2
 
< 0.1%
0.9897 1
 
< 0.1%
0.9876 7
 
< 0.1%
0.9814 9
 
< 0.1%

BASEMENTAREA_AVG
Real number (ℝ)

Zeros 

Distinct3780
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08133708355
Minimum0
Maximum1
Zeros14745
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:18.896141image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0018
Q10.0763
median0.0763
Q30.0763
95-th percentile0.1565
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0534326937
Coefficient of variation (CV)0.6569290583
Kurtosis67.99396869
Mean0.08133708355
Median Absolute Deviation (MAD)0
Skewness5.827628863
Sum25012.0479
Variance0.002855052756
MonotonicityNot monotonic
2024-12-02T17:03:19.322242image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0763 180028
58.5%
0 14745
 
4.8%
0.0818 251
 
0.1%
0.0545 251
 
0.1%
0.0727 248
 
0.1%
0.1091 246
 
0.1%
0.0796 245
 
0.1%
0.08 239
 
0.1%
0.0805 230
 
0.1%
0.0764 220
 
0.1%
Other values (3770) 110808
36.0%
ValueCountFrequency (%)
0 14745
4.8%
0.0001 99
 
< 0.1%
0.0002 38
 
< 0.1%
0.0003 8
 
< 0.1%
0.0004 33
 
< 0.1%
ValueCountFrequency (%)
1 130
< 0.1%
0.9945 1
 
< 0.1%
0.9694 2
 
< 0.1%
0.9682 1
 
< 0.1%
0.9677 1
 
< 0.1%

YEARS_BEGINEXPLUATATION_AVG
Real number (ℝ)

Skewed 

Distinct285
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9796203137
Minimum0
Maximum1
Zeros514
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:19.776433image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9722
Q10.9816
median0.9816
Q30.9821
95-th percentile0.9911
Maximum1
Range1
Interquartile range (IQR)0.0005

Descriptive statistics

Standard deviation0.0424285527
Coefficient of variation (CV)0.04331122181
Kurtosis489.2114033
Mean0.9796203137
Median Absolute Deviation (MAD)0
Skewness-21.74476589
Sum301244.0223
Variance0.001800182084
MonotonicityNot monotonic
2024-12-02T17:03:20.201361image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9816 153989
50.1%
0.9871 4311
 
1.4%
0.9856 4189
 
1.4%
0.9861 4171
 
1.4%
0.9801 4123
 
1.3%
0.9866 4114
 
1.3%
0.9851 4096
 
1.3%
0.9806 4096
 
1.3%
0.9811 3986
 
1.3%
0.9831 3970
 
1.3%
Other values (275) 116466
37.9%
ValueCountFrequency (%)
0 514
0.2%
0.0179 1
 
< 0.1%
0.0447 1
 
< 0.1%
0.0969 1
 
< 0.1%
0.0974 1
 
< 0.1%
ValueCountFrequency (%)
1 186
 
0.1%
0.9995 691
0.2%
0.999 906
0.3%
0.9985 1062
0.3%
0.998 1096
0.4%

YEARS_BUILD_AVG
Real number (ℝ)

Distinct149
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7542858694
Minimum0
Maximum1
Zeros102
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:20.643172image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6532
Q10.7552
median0.7552
Q30.7552
95-th percentile0.8504
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06558010195
Coefficient of variation (CV)0.08694329909
Kurtosis19.25836716
Mean0.7542858694
Median Absolute Deviation (MAD)0
Skewness-1.744864492
Sum231951.202
Variance0.004300749772
MonotonicityNot monotonic
2024-12-02T17:03:21.109653image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7552 207106
67.3%
0.8232 2999
 
1.0%
0.8164 2864
 
0.9%
0.8028 2848
 
0.9%
0.728 2802
 
0.9%
0.7348 2761
 
0.9%
0.8096 2755
 
0.9%
0.83 2738
 
0.9%
0.796 2734
 
0.9%
0.7484 2731
 
0.9%
Other values (139) 75173
 
24.4%
ValueCountFrequency (%)
0 102
< 0.1%
0.0004 2
 
< 0.1%
0.0072 4
 
< 0.1%
0.014 3
 
< 0.1%
0.0208 1
 
< 0.1%
ValueCountFrequency (%)
1 173
 
0.1%
0.9932 478
0.2%
0.9864 661
0.2%
0.9796 786
0.3%
0.9728 813
0.3%

COMMONAREA_AVG
Real number (ℝ)

Zeros 

Distinct3181
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02818625122
Minimum0
Maximum1
Zeros8442
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:21.519340image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0038
Q10.0211
median0.0211
Q30.0211
95-th percentile0.0727
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0431075329
Coefficient of variation (CV)1.529381561
Kurtosis154.4375736
Mean0.02818625122
Median Absolute Deviation (MAD)0
Skewness10.10817986
Sum8667.5823
Variance0.001858259393
MonotonicityNot monotonic
2024-12-02T17:03:21.936118image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0211 214971
69.9%
0 8442
 
2.7%
0.0079 544
 
0.2%
0.0078 475
 
0.2%
0.008 446
 
0.1%
0.0077 414
 
0.1%
0.0086 365
 
0.1%
0.0014 345
 
0.1%
0.007 343
 
0.1%
0.0013 317
 
0.1%
Other values (3171) 80849
 
26.3%
ValueCountFrequency (%)
0 8442
2.7%
0.0001 45
 
< 0.1%
0.0002 67
 
< 0.1%
0.0003 84
 
< 0.1%
0.0004 62
 
< 0.1%
ValueCountFrequency (%)
1 92
< 0.1%
0.9937 2
 
< 0.1%
0.9906 2
 
< 0.1%
0.9833 1
 
< 0.1%
0.9601 1
 
< 0.1%

ELEVATORS_AVG
Real number (ℝ)

Zeros 

Distinct257
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03686885998
Minimum0
Maximum1
Zeros249609
Zeros (%)81.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:22.369988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.24
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1000478357
Coefficient of variation (CV)2.713613488
Kurtosis19.20366483
Mean0.03686885998
Median Absolute Deviation (MAD)0
Skewness3.846930124
Sum11337.58
Variance0.01000956943
MonotonicityNot monotonic
2024-12-02T17:03:22.813277image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 249609
81.2%
0.08 9886
 
3.2%
0.16 8806
 
2.9%
0.24 6071
 
2.0%
0.12 5593
 
1.8%
0.04 4585
 
1.5%
0.2 4072
 
1.3%
0.32 2788
 
0.9%
0.28 2272
 
0.7%
0.4 1532
 
0.5%
Other values (247) 12297
 
4.0%
ValueCountFrequency (%)
0 249609
81.2%
0.002 1
 
< 0.1%
0.0024 1
 
< 0.1%
0.0048 3
 
< 0.1%
0.0064 5
 
< 0.1%
ValueCountFrequency (%)
1 158
0.1%
0.96 81
< 0.1%
0.9332 2
 
< 0.1%
0.92 20
 
< 0.1%
0.9 6
 
< 0.1%

ENTRANCES_AVG
Real number (ℝ)

Distinct285
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1437710944
Minimum0
Maximum1
Zeros323
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:23.239609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0345
Q10.1379
median0.1379
Q30.1379
95-th percentile0.2759
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07074560014
Coefficient of variation (CV)0.4920710971
Kurtosis27.1586059
Mean0.1437710944
Median Absolute Deviation (MAD)0
Skewness3.620689997
Sum44211.193
Variance0.005004939939
MonotonicityNot monotonic
2024-12-02T17:03:24.011997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1379 188835
61.4%
0.069 22956
 
7.5%
0.1034 19533
 
6.4%
0.2069 19062
 
6.2%
0.0345 15380
 
5.0%
0.1724 9185
 
3.0%
0.2759 7895
 
2.6%
0.2414 4165
 
1.4%
0.3448 2066
 
0.7%
0.3103 2049
 
0.7%
Other values (275) 16385
 
5.3%
ValueCountFrequency (%)
0 323
0.1%
0.0055 1
 
< 0.1%
0.0086 2
 
< 0.1%
0.0114 1
 
< 0.1%
0.0172 7
 
< 0.1%
ValueCountFrequency (%)
1 153
< 0.1%
0.9655 25
 
< 0.1%
0.931 21
 
< 0.1%
0.8966 52
 
< 0.1%
0.8621 14
 
< 0.1%

FLOORSMAX_AVG
Real number (ℝ)

Distinct403
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1966334606
Minimum0
Maximum1
Zeros2938
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:24.461045image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.1667
median0.1667
Q30.1667
95-th percentile0.375
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1067612007
Coefficient of variation (CV)0.5429452362
Kurtosis8.329744876
Mean0.1966334606
Median Absolute Deviation (MAD)0
Skewness2.300269688
Sum60466.9521
Variance0.01139795398
MonotonicityNot monotonic
2024-12-02T17:03:24.908619image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1667 214895
69.9%
0.3333 31909
 
10.4%
0.0417 14600
 
4.7%
0.375 7926
 
2.6%
0.125 6974
 
2.3%
0.0833 6586
 
2.1%
0 2938
 
1.0%
0.4583 2828
 
0.9%
0.625 1915
 
0.6%
0.5417 1685
 
0.5%
Other values (393) 15255
 
5.0%
ValueCountFrequency (%)
0 2938
1.0%
0.0067 1
 
< 0.1%
0.0083 3
 
< 0.1%
0.01 4
 
< 0.1%
0.0104 5
 
< 0.1%
ValueCountFrequency (%)
1 167
0.1%
0.9792 1
 
< 0.1%
0.9583 83
< 0.1%
0.9479 2
 
< 0.1%
0.9375 4
 
< 0.1%

FLOORSMIN_AVG
Real number (ℝ)

Distinct305
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2158856337
Minimum0
Maximum1
Zeros2320
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:25.342355image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.2083
median0.2083
Q30.2083
95-th percentile0.375
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09216694758
Coefficient of variation (CV)0.4269248769
Kurtosis11.43288466
Mean0.2158856337
Median Absolute Deviation (MAD)0
Skewness2.16176346
Sum66387.2071
Variance0.008494746227
MonotonicityNot monotonic
2024-12-02T17:03:25.777754image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2083 241517
78.5%
0.375 17845
 
5.8%
0.0417 17776
 
5.8%
0.0833 5086
 
1.7%
0.4167 3961
 
1.3%
0.1667 3537
 
1.2%
0.125 3336
 
1.1%
0 2320
 
0.8%
0.5 1688
 
0.5%
0.6667 1194
 
0.4%
Other values (295) 9251
 
3.0%
ValueCountFrequency (%)
0 2320
0.8%
0.0067 3
 
< 0.1%
0.0104 3
 
< 0.1%
0.0138 1
 
< 0.1%
0.0158 4
 
< 0.1%
ValueCountFrequency (%)
1 141
< 0.1%
0.9792 5
 
< 0.1%
0.9583 10
 
< 0.1%
0.9408 2
 
< 0.1%
0.9304 1
 
< 0.1%

LANDAREA_AVG
Real number (ℝ)

Zeros 

Distinct3527
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05550691422
Minimum0
Maximum1
Zeros15600
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:26.201085image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0481
median0.0481
Q30.0481
95-th percentile0.1266
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05251255146
Coefficient of variation (CV)0.9460542383
Kurtosis90.35473469
Mean0.05550691422
Median Absolute Deviation (MAD)0
Skewness7.294944989
Sum17068.9867
Variance0.002757568061
MonotonicityNot monotonic
2024-12-02T17:03:26.642691image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0481 182700
59.4%
0 15600
 
5.1%
0.0631 189
 
0.1%
0.0316 187
 
0.1%
0.0473 186
 
0.1%
0.0174 180
 
0.1%
0.0237 175
 
0.1%
0.0552 173
 
0.1%
0.0331 170
 
0.1%
0.0158 170
 
0.1%
Other values (3517) 107781
35.0%
ValueCountFrequency (%)
0 15600
5.1%
0.0001 13
 
< 0.1%
0.0002 13
 
< 0.1%
0.0003 9
 
< 0.1%
0.0004 11
 
< 0.1%
ValueCountFrequency (%)
1 135
< 0.1%
0.9829 10
 
< 0.1%
0.9777 3
 
< 0.1%
0.969 1
 
< 0.1%
0.9497 1
 
< 0.1%

LIVINGAPARTMENTS_AVG
Real number (ℝ)

Distinct1868
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08356656933
Minimum0
Maximum1
Zeros418
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:27.069071image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0336
Q10.0756
median0.0756
Q30.0756
95-th percentile0.1673
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05337752382
Coefficient of variation (CV)0.6387425528
Kurtosis59.87917491
Mean0.08356656933
Median Absolute Deviation (MAD)0
Skewness5.951298762
Sum25697.6393
Variance0.002849160049
MonotonicityNot monotonic
2024-12-02T17:03:27.481410image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0756 212977
69.3%
0.0504 4272
 
1.4%
0.0672 4231
 
1.4%
0.0588 2586
 
0.8%
0.0841 1864
 
0.6%
0.121 1793
 
0.6%
0.0067 1695
 
0.6%
0.0605 1492
 
0.5%
0.1009 1456
 
0.5%
0.0134 1447
 
0.5%
Other values (1858) 73698
 
24.0%
ValueCountFrequency (%)
0 418
0.1%
0.0008 117
 
< 0.1%
0.0013 1
 
< 0.1%
0.0017 250
0.1%
0.0021 2
 
< 0.1%
ValueCountFrequency (%)
1 92
< 0.1%
0.9994 3
 
< 0.1%
0.9901 3
 
< 0.1%
0.9641 2
 
< 0.1%
0.949 4
 
< 0.1%

LIVINGAREA_AVG
Real number (ℝ)

Distinct5199
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09088590717
Minimum0
Maximum1
Zeros284
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:27.894728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0144
Q10.0745
median0.0745
Q30.0745
95-th percentile0.2323
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07974451033
Coefficient of variation (CV)0.8774133726
Kurtosis28.6043449
Mean0.09088590717
Median Absolute Deviation (MAD)0
Skewness4.384472312
Sum27948.4162
Variance0.006359186928
MonotonicityNot monotonic
2024-12-02T17:03:28.329685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0745 154422
50.2%
0 284
 
0.1%
0.0512 243
 
0.1%
0.051 223
 
0.1%
0.0702 223
 
0.1%
0.0509 221
 
0.1%
0.0538 220
 
0.1%
0.0638 215
 
0.1%
0.0513 210
 
0.1%
0.0511 209
 
0.1%
Other values (5189) 151041
49.1%
ValueCountFrequency (%)
0 284
0.1%
0.0001 4
 
< 0.1%
0.0002 8
 
< 0.1%
0.0003 10
 
< 0.1%
0.0004 14
 
< 0.1%
ValueCountFrequency (%)
1 150
< 0.1%
0.9984 1
 
< 0.1%
0.9978 1
 
< 0.1%
0.9893 1
 
< 0.1%
0.986 1
 
< 0.1%

NONLIVINGAPARTMENTS_AVG
Real number (ℝ)

Skewed  Zeros 

Distinct386
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002692550185
Minimum0
Maximum1
Zeros268063
Zeros (%)87.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:28.752067image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0116
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02669972295
Coefficient of variation (CV)9.916146817
Kurtosis920.4662852
Mean0.002692550185
Median Absolute Deviation (MAD)0
Skewness27.81539184
Sum827.9888
Variance0.0007128752056
MonotonicityNot monotonic
2024-12-02T17:03:29.178110image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 268063
87.2%
0.0039 13606
 
4.4%
0.0077 6351
 
2.1%
0.0116 3714
 
1.2%
0.0154 2533
 
0.8%
0.0193 1673
 
0.5%
0.0019 1250
 
0.4%
0.0232 1195
 
0.4%
0.027 865
 
0.3%
0.0309 717
 
0.2%
Other values (376) 7544
 
2.5%
ValueCountFrequency (%)
0 268063
87.2%
0.0002 1
 
< 0.1%
0.0003 5
 
< 0.1%
0.0004 25
 
< 0.1%
0.0005 6
 
< 0.1%
ValueCountFrequency (%)
1 97
< 0.1%
0.9961 2
 
< 0.1%
0.9923 4
 
< 0.1%
0.9884 1
 
< 0.1%
0.973 3
 
< 0.1%

NONLIVINGAREA_AVG
Real number (ℝ)

Zeros 

Distinct3290
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01469663362
Minimum0
Maximum1
Zeros58735
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:29.618304image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0036
median0.0036
Q30.0036
95-th percentile0.0737
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04814548059
Coefficient of variation (CV)3.275952973
Kurtosis139.8497524
Mean0.01469663362
Median Absolute Deviation (MAD)0
Skewness9.650938792
Sum4519.3765
Variance0.002317987301
MonotonicityNot monotonic
2024-12-02T17:03:30.043701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0036 170081
55.3%
0 58735
 
19.1%
0.0012 546
 
0.2%
0.0044 454
 
0.1%
0.0022 440
 
0.1%
0.0031 415
 
0.1%
0.0011 405
 
0.1%
0.001 405
 
0.1%
0.003 397
 
0.1%
0.0024 395
 
0.1%
Other values (3280) 75238
24.5%
ValueCountFrequency (%)
0 58735
19.1%
0.0001 163
 
0.1%
0.0002 107
 
< 0.1%
0.0003 95
 
< 0.1%
0.0004 162
 
0.1%
ValueCountFrequency (%)
1 136
< 0.1%
0.9956 1
 
< 0.1%
0.9823 1
 
< 0.1%
0.9764 1
 
< 0.1%
0.9591 2
 
< 0.1%

APARTMENTS_MODE
Real number (ℝ)

Distinct760
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09888885276
Minimum0
Maximum1
Zeros976
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:30.470523image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0168
Q10.084
median0.084
Q30.084
95-th percentile0.229
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07724090874
Coefficient of variation (CV)0.7810881266
Kurtosis27.80713812
Mean0.09888885276
Median Absolute Deviation (MAD)0
Skewness4.205881702
Sum30409.41
Variance0.005966157983
MonotonicityNot monotonic
2024-12-02T17:03:30.902772image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.084 163583
53.2%
0.063 7451
 
2.4%
0.0945 4757
 
1.5%
0.0735 4388
 
1.4%
0.0084 3970
 
1.3%
0.0168 3324
 
1.1%
0.105 3116
 
1.0%
0.1513 3039
 
1.0%
0.0126 3034
 
1.0%
0.0756 2973
 
1.0%
Other values (750) 107876
35.1%
ValueCountFrequency (%)
0 976
0.3%
0.0011 285
 
0.1%
0.0021 1006
0.3%
0.0032 431
0.1%
0.0042 1069
0.3%
ValueCountFrequency (%)
1 150
< 0.1%
0.9989 1
 
< 0.1%
0.9947 1
 
< 0.1%
0.9884 1
 
< 0.1%
0.9853 1
 
< 0.1%

BASEMENTAREA_MODE
Real number (ℝ)

Zeros 

Distinct3841
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07996936793
Minimum0
Maximum1
Zeros16598
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:31.327089image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0746
median0.0746
Q30.0746
95-th percentile0.1578
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05467371107
Coefficient of variation (CV)0.6836831714
Kurtosis64.38447521
Mean0.07996936793
Median Absolute Deviation (MAD)0
Skewness5.705940034
Sum24591.4603
Variance0.002989214683
MonotonicityNot monotonic
2024-12-02T17:03:31.736458image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0746 180035
58.5%
0 16598
 
5.4%
0.0566 269
 
0.1%
0.0849 265
 
0.1%
0.0642 253
 
0.1%
0.083 251
 
0.1%
0.1132 243
 
0.1%
0.0792 241
 
0.1%
0.0826 238
 
0.1%
0.0679 222
 
0.1%
Other values (3831) 108896
35.4%
ValueCountFrequency (%)
0 16598
5.4%
0.0001 105
 
< 0.1%
0.0002 41
 
< 0.1%
0.0003 10
 
< 0.1%
0.0004 33
 
< 0.1%
ValueCountFrequency (%)
1 133
< 0.1%
0.991 2
 
< 0.1%
0.9842 2
 
< 0.1%
0.9787 4
 
< 0.1%
0.9578 1
 
< 0.1%

YEARS_BEGINEXPLUATATION_MODE
Real number (ℝ)

Skewed 

Distinct221
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9792774102
Minimum0
Maximum1
Zeros142
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:32.145234image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9722
Q10.9811
median0.9816
Q30.9816
95-th percentile0.9906
Maximum1
Range1
Interquartile range (IQR)0.0005

Descriptive statistics

Standard deviation0.04627046504
Coefficient of variation (CV)0.0472495991
Kurtosis434.1615313
Mean0.9792774102
Median Absolute Deviation (MAD)0
Skewness-20.68616897
Sum301138.5757
Variance0.002140955935
MonotonicityNot monotonic
2024-12-02T17:03:32.559610image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9816 153983
50.1%
0.9871 4291
 
1.4%
0.9866 4173
 
1.4%
0.9861 4167
 
1.4%
0.9801 4110
 
1.3%
0.9806 4083
 
1.3%
0.9856 4075
 
1.3%
0.9851 4016
 
1.3%
0.9796 3974
 
1.3%
0.9791 3935
 
1.3%
Other values (211) 116704
38.0%
ValueCountFrequency (%)
0 142
 
< 0.1%
0.0005 525
0.2%
0.0184 1
 
< 0.1%
0.0452 1
 
< 0.1%
0.0973 1
 
< 0.1%
ValueCountFrequency (%)
1 211
 
0.1%
0.9995 702
0.2%
0.999 915
0.3%
0.9985 1053
0.3%
0.998 1065
0.3%

YEARS_BUILD_MODE
Real number (ℝ)

Distinct154
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7630703887
Minimum0
Maximum1
Zeros103
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:33.002251image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6602
Q10.7648
median0.7648
Q30.7648
95-th percentile0.8563
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06377983392
Coefficient of variation (CV)0.08358315938
Kurtosis20.49726102
Mean0.7630703887
Median Absolute Deviation (MAD)0
Skewness-1.889139715
Sum234652.5383
Variance0.004067867215
MonotonicityNot monotonic
2024-12-02T17:03:33.428242image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7648 207013
67.3%
0.8301 2960
 
1.0%
0.8236 2879
 
0.9%
0.7387 2789
 
0.9%
0.8171 2763
 
0.9%
0.8105 2755
 
0.9%
0.7452 2737
 
0.9%
0.8367 2711
 
0.9%
0.804 2707
 
0.9%
0.7583 2704
 
0.9%
Other values (144) 75493
 
24.5%
ValueCountFrequency (%)
0 103
< 0.1%
0.0003 3
 
< 0.1%
0.0134 2
 
< 0.1%
0.0199 2
 
< 0.1%
0.0265 2
 
< 0.1%
ValueCountFrequency (%)
1 183
 
0.1%
0.9935 487
0.2%
0.9869 653
0.2%
0.9804 791
0.3%
0.9739 779
0.3%

COMMONAREA_MODE
Real number (ℝ)

Zeros 

Distinct3128
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02609601933
Minimum0
Maximum1
Zeros9690
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:33.835966image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0029
Q10.019
median0.019
Q30.019
95-th percentile0.0695
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04226631245
Coefficient of variation (CV)1.619645967
Kurtosis162.6301843
Mean0.02609601933
Median Absolute Deviation (MAD)0
Skewness10.35860244
Sum8024.813
Variance0.001786441168
MonotonicityNot monotonic
2024-12-02T17:03:34.253143image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.019 214993
69.9%
0 9690
 
3.2%
0.008 546
 
0.2%
0.0079 543
 
0.2%
0.0078 518
 
0.2%
0.0081 416
 
0.1%
0.0087 397
 
0.1%
0.0014 394
 
0.1%
0.007 363
 
0.1%
0.0071 341
 
0.1%
Other values (3118) 79310
 
25.8%
ValueCountFrequency (%)
0 9690
3.2%
0.0001 60
 
< 0.1%
0.0002 52
 
< 0.1%
0.0003 68
 
< 0.1%
0.0004 63
 
< 0.1%
ValueCountFrequency (%)
1 89
< 0.1%
0.9997 2
 
< 0.1%
0.9923 1
 
< 0.1%
0.9689 1
 
< 0.1%
0.9639 1
 
< 0.1%

ELEVATORS_MODE
Real number (ℝ)

Zeros 

Distinct26
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03478970151
Minimum0
Maximum1
Zeros253389
Zeros (%)82.4%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:34.628684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.2417
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09772639303
Coefficient of variation (CV)2.809060981
Kurtosis20.83874137
Mean0.03478970151
Median Absolute Deviation (MAD)0
Skewness4.004276973
Sum10698.2159
Variance0.009550447895
MonotonicityNot monotonic
2024-12-02T17:03:35.038609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 253389
82.4%
0.0806 11629
 
3.8%
0.1611 9675
 
3.1%
0.2417 6379
 
2.1%
0.1208 5734
 
1.9%
0.0403 4876
 
1.6%
0.2014 3962
 
1.3%
0.3222 2887
 
0.9%
0.282 2135
 
0.7%
0.4028 1554
 
0.5%
Other values (16) 5291
 
1.7%
ValueCountFrequency (%)
0 253389
82.4%
0.0403 4876
 
1.6%
0.0806 11629
 
3.8%
0.1208 5734
 
1.9%
0.1611 9675
 
3.1%
ValueCountFrequency (%)
1 144
< 0.1%
0.9667 87
< 0.1%
0.9264 20
 
< 0.1%
0.8862 66
< 0.1%
0.8459 34
 
< 0.1%

ENTRANCES_MODE
Real number (ℝ)

Distinct30
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1415208949
Minimum0
Maximum1
Zeros387
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:35.428994image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0345
Q10.1379
median0.1379
Q30.1379
95-th percentile0.2759
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07124530071
Coefficient of variation (CV)0.503426019
Kurtosis26.60823875
Mean0.1415208949
Median Absolute Deviation (MAD)0
Skewness3.536007776
Sum43519.2319
Variance0.005075892874
MonotonicityNot monotonic
2024-12-02T17:03:35.806737image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.1379 190869
62.1%
0.069 26704
 
8.7%
0.1034 20533
 
6.7%
0.2069 19678
 
6.4%
0.0345 19428
 
6.3%
0.1724 8986
 
2.9%
0.2759 8036
 
2.6%
0.2414 4013
 
1.3%
0.3448 2046
 
0.7%
0.3103 2014
 
0.7%
Other values (20) 5204
 
1.7%
ValueCountFrequency (%)
0 387
 
0.1%
0.0345 19428
 
6.3%
0.069 26704
 
8.7%
0.1034 20533
 
6.7%
0.1379 190869
62.1%
ValueCountFrequency (%)
1 152
< 0.1%
0.9655 25
 
< 0.1%
0.931 21
 
< 0.1%
0.8966 52
 
< 0.1%
0.8621 14
 
< 0.1%

FLOORSMAX_MODE
Real number (ℝ)

Zeros 

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1946405429
Minimum0
Maximum1
Zeros3415
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:36.174499image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.1667
median0.1667
Q30.1667
95-th percentile0.375
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1055878905
Coefficient of variation (CV)0.5424763459
Kurtosis8.583989219
Mean0.1946405429
Median Absolute Deviation (MAD)0
Skewness2.307720857
Sum59854.108
Variance0.01114880262
MonotonicityNot monotonic
2024-12-02T17:03:36.537895image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.1667 218570
71.1%
0.3333 34373
 
11.2%
0.0417 15616
 
5.1%
0.375 8321
 
2.7%
0.125 7267
 
2.4%
0.0833 6785
 
2.2%
0 3415
 
1.1%
0.4583 3216
 
1.0%
0.625 2075
 
0.7%
0.5417 1836
 
0.6%
Other values (15) 6037
 
2.0%
ValueCountFrequency (%)
0 3415
 
1.1%
0.0417 15616
 
5.1%
0.0833 6785
 
2.2%
0.125 7267
 
2.4%
0.1667 218570
71.1%
ValueCountFrequency (%)
1 164
0.1%
0.9583 94
< 0.1%
0.9167 38
 
< 0.1%
0.875 229
0.1%
0.8333 22
 
< 0.1%

FLOORSMIN_MODE
Real number (ℝ)

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2146526261
Minimum0
Maximum1
Zeros2517
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:36.895728image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.2083
median0.2083
Q30.2083
95-th percentile0.375
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09184558255
Coefficient of variation (CV)0.4278800787
Kurtosis11.37323608
Mean0.2146526261
Median Absolute Deviation (MAD)0
Skewness2.108366567
Sum66008.0437
Variance0.008435611034
MonotonicityNot monotonic
2024-12-02T17:03:37.601138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.2083 243045
79.0%
0.375 19042
 
6.2%
0.0417 18917
 
6.2%
0.0833 5349
 
1.7%
0.4167 4105
 
1.3%
0.1667 3636
 
1.2%
0.125 3170
 
1.0%
0 2517
 
0.8%
0.5 1889
 
0.6%
0.6667 1264
 
0.4%
Other values (15) 4577
 
1.5%
ValueCountFrequency (%)
0 2517
 
0.8%
0.0417 18917
6.2%
0.0833 5349
 
1.7%
0.125 3170
 
1.0%
0.1667 3636
 
1.2%
ValueCountFrequency (%)
1 141
< 0.1%
0.9583 17
 
< 0.1%
0.9167 131
< 0.1%
0.875 9
 
< 0.1%
0.8333 22
 
< 0.1%

LANDAREA_MODE
Real number (ℝ)

Zeros 

Distinct3563
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0535824764
Minimum0
Maximum1
Zeros17453
Zeros (%)5.7%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:38.013500image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0458
median0.0458
Q30.0458
95-th percentile0.12645
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05294724856
Coefficient of variation (CV)0.9881448585
Kurtosis86.6332682
Mean0.0535824764
Median Absolute Deviation (MAD)0
Skewness7.170948134
Sum16477.2009
Variance0.00280341113
MonotonicityNot monotonic
2024-12-02T17:03:38.421247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0458 182684
59.4%
0 17453
 
5.7%
0.0194 208
 
0.1%
0.0645 193
 
0.1%
0.0484 192
 
0.1%
0.0323 188
 
0.1%
0.0147 178
 
0.1%
0.0111 175
 
0.1%
0.0144 175
 
0.1%
0.0258 173
 
0.1%
Other values (3553) 105892
34.4%
ValueCountFrequency (%)
0 17453
5.7%
0.0001 24
 
< 0.1%
0.0002 14
 
< 0.1%
0.0003 6
 
< 0.1%
0.0004 14
 
< 0.1%
ValueCountFrequency (%)
1 129
< 0.1%
0.9911 1
 
< 0.1%
0.9714 1
 
< 0.1%
0.9665 2
 
< 0.1%
0.9587 3
 
< 0.1%

LIVINGAPARTMENTS_MODE
Real number (ℝ)

Distinct736
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08613303329
Minimum0
Maximum1
Zeros519
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:38.830030image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0331
Q10.0771
median0.0771
Q30.0771
95-th percentile0.1736
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05663929584
Coefficient of variation (CV)0.6575792548
Kurtosis52.82388401
Mean0.08613303329
Median Absolute Deviation (MAD)0
Skewness5.727419652
Sum26486.8552
Variance0.003208009833
MonotonicityNot monotonic
2024-12-02T17:03:39.254547image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0771 210689
68.5%
0.0551 4931
 
1.6%
0.0735 4797
 
1.6%
0.0826 2966
 
1.0%
0.0643 2853
 
0.9%
0.0918 2069
 
0.7%
0.1322 1972
 
0.6%
0.0661 1930
 
0.6%
0.0073 1883
 
0.6%
0.0147 1585
 
0.5%
Other values (726) 71836
 
23.4%
ValueCountFrequency (%)
0 519
0.2%
0.0009 156
 
0.1%
0.0018 295
0.1%
0.0028 146
 
< 0.1%
0.0037 413
0.1%
ValueCountFrequency (%)
1 94
< 0.1%
0.9826 1
 
< 0.1%
0.9816 2
 
< 0.1%
0.978 1
 
< 0.1%
0.9761 1
 
< 0.1%

LIVINGAREA_MODE
Real number (ℝ)

Distinct5301
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08947396906
Minimum0
Maximum1
Zeros444
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:39.669513image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0134
Q10.0731
median0.0731
Q30.0731
95-th percentile0.2333
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.08062671084
Coefficient of variation (CV)0.9011191935
Kurtosis28.91301484
Mean0.08947396906
Median Absolute Deviation (MAD)0
Skewness4.447489937
Sum27514.2297
Variance0.006500666501
MonotonicityNot monotonic
2024-12-02T17:03:40.104929image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0731 154569
50.3%
0 444
 
0.1%
0.053 272
 
0.1%
0.0532 262
 
0.1%
0.0529 249
 
0.1%
0.0533 242
 
0.1%
0.0561 224
 
0.1%
0.0656 224
 
0.1%
0.0734 223
 
0.1%
0.0536 222
 
0.1%
Other values (5291) 150580
49.0%
ValueCountFrequency (%)
0 444
0.1%
0.0001 7
 
< 0.1%
0.0002 7
 
< 0.1%
0.0003 16
 
< 0.1%
0.0004 24
 
< 0.1%
ValueCountFrequency (%)
1 150
< 0.1%
0.995 3
 
< 0.1%
0.9922 13
 
< 0.1%
0.9886 2
 
< 0.1%
0.9868 1
 
< 0.1%

NONLIVINGAPARTMENTS_MODE
Real number (ℝ)

Skewed  Zeros 

Distinct167
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002468712339
Minimum0
Maximum1
Zeros272769
Zeros (%)88.7%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:40.529536image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0078
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02585401013
Coefficient of variation (CV)10.4726702
Kurtosis1003.102409
Mean0.002468712339
Median Absolute Deviation (MAD)0
Skewness29.12609052
Sum759.1562
Variance0.0006684298399
MonotonicityNot monotonic
2024-12-02T17:03:40.959007image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 272769
88.7%
0.0039 14105
 
4.6%
0.0078 6413
 
2.1%
0.0117 3675
 
1.2%
0.0156 2492
 
0.8%
0.0195 1653
 
0.5%
0.0233 1177
 
0.4%
0.0272 840
 
0.3%
0.0311 711
 
0.2%
0.035 527
 
0.2%
Other values (157) 3149
 
1.0%
ValueCountFrequency (%)
0 272769
88.7%
0.0039 14105
 
4.6%
0.0078 6413
 
2.1%
0.0117 3675
 
1.2%
0.0156 2492
 
0.8%
ValueCountFrequency (%)
1 100
< 0.1%
0.9961 1
 
< 0.1%
0.9805 3
 
< 0.1%
0.965 2
 
< 0.1%
0.9533 2
 
< 0.1%

NONLIVINGAREA_MODE
Real number (ℝ)

Zeros 

Distinct3327
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01271860031
Minimum0
Maximum1
Zeros67126
Zeros (%)21.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:41.383813image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0011
median0.0011
Q30.0011
95-th percentile0.071
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04876843405
Coefficient of variation (CV)3.834418321
Kurtosis135.8181434
Mean0.01271860031
Median Absolute Deviation (MAD)0
Skewness9.561626269
Sum3911.1095
Variance0.002378360159
MonotonicityNot monotonic
2024-12-02T17:03:41.811487image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0011 170159
55.3%
0 67126
 
21.8%
0.0046 466
 
0.2%
0.0033 430
 
0.1%
0.0012 427
 
0.1%
0.0023 426
 
0.1%
0.0013 410
 
0.1%
0.003 370
 
0.1%
0.0055 363
 
0.1%
0.0037 357
 
0.1%
Other values (3317) 66977
 
21.8%
ValueCountFrequency (%)
0 67126
21.8%
0.0001 123
 
< 0.1%
0.0002 125
 
< 0.1%
0.0003 61
 
< 0.1%
0.0004 90
 
< 0.1%
ValueCountFrequency (%)
1 135
< 0.1%
0.9878 1
 
< 0.1%
0.9852 1
 
< 0.1%
0.984 5
 
< 0.1%
0.9752 1
 
< 0.1%

APARTMENTS_MEDI
Real number (ℝ)

Distinct1148
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1018891711
Minimum0
Maximum1
Zeros771
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:42.235692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0167
Q10.0864
median0.0864
Q30.0864
95-th percentile0.2405
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07814587095
Coefficient of variation (CV)0.7669693461
Kurtosis26.75325955
Mean0.1018891711
Median Absolute Deviation (MAD)0
Skewness4.122884523
Sum31332.0409
Variance0.006106777146
MonotonicityNot monotonic
2024-12-02T17:03:42.685495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0864 156448
50.9%
0.0833 7109
 
2.3%
0.0625 6687
 
2.2%
0.0937 4622
 
1.5%
0.0729 4211
 
1.4%
0.0083 3562
 
1.2%
0.0167 3098
 
1.0%
0.1041 3097
 
1.0%
0.1499 2992
 
1.0%
0.0125 2801
 
0.9%
Other values (1138) 112884
36.7%
ValueCountFrequency (%)
0 771
0.3%
0.001 199
 
0.1%
0.0016 6
 
< 0.1%
0.0021 808
0.3%
0.0026 13
 
< 0.1%
ValueCountFrequency (%)
1 142
< 0.1%
0.9993 1
 
< 0.1%
0.9972 7
 
< 0.1%
0.991 9
 
< 0.1%
0.9899 1
 
< 0.1%

BASEMENTAREA_MEDI
Real number (ℝ)

Zeros 

Distinct3772
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08084232532
Minimum0
Maximum1
Zeros14991
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:43.127576image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0011
Q10.0758
median0.0758
Q30.0758
95-th percentile0.1557
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05326736686
Coefficient of variation (CV)0.6589044372
Kurtosis67.74537422
Mean0.08084232532
Median Absolute Deviation (MAD)0
Skewness5.808158757
Sum24859.9043
Variance0.002837412372
MonotonicityNot monotonic
2024-12-02T17:03:43.546423image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0758 180030
58.5%
0 14991
 
4.9%
0.0818 271
 
0.1%
0.1091 266
 
0.1%
0.0545 265
 
0.1%
0.0727 248
 
0.1%
0.0796 246
 
0.1%
0.08 240
 
0.1%
0.0805 234
 
0.1%
0.0655 221
 
0.1%
Other values (3762) 110499
35.9%
ValueCountFrequency (%)
0 14991
4.9%
0.0001 106
 
< 0.1%
0.0002 39
 
< 0.1%
0.0003 8
 
< 0.1%
0.0004 31
 
< 0.1%
ValueCountFrequency (%)
1 130
< 0.1%
0.9945 1
 
< 0.1%
0.9694 2
 
< 0.1%
0.9682 1
 
< 0.1%
0.9677 1
 
< 0.1%

YEARS_BEGINEXPLUATATION_MEDI
Real number (ℝ)

Skewed 

Distinct245
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9796292289
Minimum0
Maximum1
Zeros548
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:43.968910image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.9722
Q10.9816
median0.9816
Q30.9821
95-th percentile0.9911
Maximum1
Range1
Interquartile range (IQR)0.0005

Descriptive statistics

Standard deviation0.04291003388
Coefficient of variation (CV)0.04380232093
Kurtosis489.656571
Mean0.9796292289
Median Absolute Deviation (MAD)0
Skewness-21.82538695
Sum301246.7638
Variance0.001841271008
MonotonicityNot monotonic
2024-12-02T17:03:44.386921image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9816 153937
50.1%
0.9871 4314
 
1.4%
0.9861 4247
 
1.4%
0.9856 4199
 
1.4%
0.9866 4138
 
1.3%
0.9801 4115
 
1.3%
0.9806 4069
 
1.3%
0.9851 4032
 
1.3%
0.9796 3963
 
1.3%
0.9876 3948
 
1.3%
Other values (235) 116549
37.9%
ValueCountFrequency (%)
0 548
0.2%
0.0179 1
 
< 0.1%
0.0447 1
 
< 0.1%
0.0969 1
 
< 0.1%
0.0974 1
 
< 0.1%
ValueCountFrequency (%)
1 206
 
0.1%
0.9995 717
0.2%
0.999 926
0.3%
0.9985 1073
0.3%
0.998 1114
0.4%

YEARS_BUILD_MEDI
Real number (ℝ)

Distinct151
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7575774402
Minimum0
Maximum1
Zeros101
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:44.804226image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6578
Q10.7585
median0.7585
Q30.7585
95-th percentile0.8524
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06487802313
Coefficient of variation (CV)0.08563880033
Kurtosis19.46756355
Mean0.7575774402
Median Absolute Deviation (MAD)0
Skewness-1.747012057
Sum232963.3962
Variance0.004209157885
MonotonicityNot monotonic
2024-12-02T17:03:45.227435image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7585 207066
67.3%
0.8256 2994
 
1.0%
0.8189 2883
 
0.9%
0.8054 2842
 
0.9%
0.7316 2799
 
0.9%
0.8121 2784
 
0.9%
0.8323 2740
 
0.9%
0.7383 2739
 
0.9%
0.7987 2700
 
0.9%
0.7518 2687
 
0.9%
Other values (141) 75277
 
24.5%
ValueCountFrequency (%)
0 101
< 0.1%
0.0003 2
 
< 0.1%
0.0071 1
 
< 0.1%
0.0138 2
 
< 0.1%
0.0205 3
 
< 0.1%
ValueCountFrequency (%)
1 182
 
0.1%
0.9933 494
0.2%
0.9866 665
0.2%
0.9799 802
0.3%
0.9732 819
0.3%

COMMONAREA_MEDI
Real number (ℝ)

Zeros 

Distinct3202
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02796891753
Minimum0
Maximum1
Zeros8691
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:45.635995image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0036
Q10.0208
median0.0208
Q30.0208
95-th percentile0.0726
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04319684825
Coefficient of variation (CV)1.544459066
Kurtosis151.9863514
Mean0.02796891753
Median Absolute Deviation (MAD)0
Skewness10.037227
Sum8600.7498
Variance0.001865967699
MonotonicityNot monotonic
2024-12-02T17:03:46.051886image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0208 214944
69.9%
0 8691
 
2.8%
0.0079 581
 
0.2%
0.008 486
 
0.2%
0.0078 481
 
0.2%
0.0014 377
 
0.1%
0.0086 376
 
0.1%
0.0081 337
 
0.1%
0.0071 336
 
0.1%
0.0087 309
 
0.1%
Other values (3192) 80593
 
26.2%
ValueCountFrequency (%)
0 8691
2.8%
0.0001 57
 
< 0.1%
0.0002 49
 
< 0.1%
0.0003 73
 
< 0.1%
0.0004 63
 
< 0.1%
ValueCountFrequency (%)
1 90
< 0.1%
0.9969 2
 
< 0.1%
0.9896 1
 
< 0.1%
0.9662 1
 
< 0.1%
0.9613 1
 
< 0.1%

ELEVATORS_MEDI
Real number (ℝ)

Zeros 

Distinct46
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03646549229
Minimum0
Maximum1
Zeros250917
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:46.451530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.24
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09981049886
Coefficient of variation (CV)2.737121936
Kurtosis19.45695325
Mean0.03646549229
Median Absolute Deviation (MAD)0
Skewness3.874946917
Sum11213.54
Variance0.009962135682
MonotonicityNot monotonic
2024-12-02T17:03:46.870968image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 250917
81.6%
0.08 10832
 
3.5%
0.16 9278
 
3.0%
0.24 6392
 
2.1%
0.12 5946
 
1.9%
0.04 4852
 
1.6%
0.2 4162
 
1.4%
0.32 2937
 
1.0%
0.28 2317
 
0.8%
0.4 1604
 
0.5%
Other values (36) 8274
 
2.7%
ValueCountFrequency (%)
0 250917
81.6%
0.02 368
 
0.1%
0.04 4852
 
1.6%
0.06 388
 
0.1%
0.08 10832
 
3.5%
ValueCountFrequency (%)
1 158
0.1%
0.96 81
< 0.1%
0.92 20
 
< 0.1%
0.9 6
 
< 0.1%
0.88 68
< 0.1%

ENTRANCES_MEDI
Real number (ℝ)

Distinct46
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.143516935
Minimum0
Maximum1
Zeros329
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:47.271593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0345
Q10.1379
median0.1379
Q30.1379
95-th percentile0.2759
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07094892437
Coefficient of variation (CV)0.4943592501
Kurtosis26.89797464
Mean0.143516935
Median Absolute Deviation (MAD)0
Skewness3.595622257
Sum44133.0362
Variance0.005033749869
MonotonicityNot monotonic
2024-12-02T17:03:47.694332image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0.1379 190363
61.9%
0.069 24193
 
7.9%
0.1034 20492
 
6.7%
0.2069 19750
 
6.4%
0.0345 16150
 
5.3%
0.1724 9566
 
3.1%
0.2759 8048
 
2.6%
0.2414 4318
 
1.4%
0.3448 2108
 
0.7%
0.3103 2086
 
0.7%
Other values (36) 10437
 
3.4%
ValueCountFrequency (%)
0 329
 
0.1%
0.0172 7
 
< 0.1%
0.0345 16150
5.3%
0.0517 611
 
0.2%
0.069 24193
7.9%
ValueCountFrequency (%)
1 153
< 0.1%
0.9655 25
 
< 0.1%
0.931 21
 
< 0.1%
0.8966 52
 
< 0.1%
0.8621 14
 
< 0.1%

FLOORSMAX_MEDI
Real number (ℝ)

Distinct49
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1964398805
Minimum0
Maximum1
Zeros2995
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:48.119988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.1667
median0.1667
Q30.1667
95-th percentile0.375
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.106997956
Coefficient of variation (CV)0.5446855075
Kurtosis8.418598341
Mean0.1964398805
Median Absolute Deviation (MAD)0
Skewness2.315270355
Sum60407.4241
Variance0.01144856259
MonotonicityNot monotonic
2024-12-02T17:03:48.537725image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0.1667 216627
70.4%
0.3333 33279
 
10.8%
0.0417 14832
 
4.8%
0.375 8207
 
2.7%
0.125 7079
 
2.3%
0.0833 6657
 
2.2%
0.4583 3089
 
1.0%
0 2995
 
1.0%
0.625 2042
 
0.7%
0.5417 1860
 
0.6%
Other values (39) 10844
 
3.5%
ValueCountFrequency (%)
0 2995
 
1.0%
0.0208 126
 
< 0.1%
0.0417 14832
4.8%
0.0625 132
 
< 0.1%
0.0833 6657
2.2%
ValueCountFrequency (%)
1 170
0.1%
0.9792 1
 
< 0.1%
0.9583 95
< 0.1%
0.9375 4
 
< 0.1%
0.9167 37
 
< 0.1%

FLOORSMIN_MEDI
Real number (ℝ)

Distinct47
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2157992872
Minimum0
Maximum1
Zeros2351
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:48.951113image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0417
Q10.2083
median0.2083
Q30.2083
95-th percentile0.375
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09246354756
Coefficient of variation (CV)0.428470125
Kurtosis11.4551164
Mean0.2157992872
Median Absolute Deviation (MAD)0
Skewness2.165891877
Sum66360.6546
Variance0.008549507628
MonotonicityNot monotonic
2024-12-02T17:03:49.375925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.2083 242379
78.8%
0.375 18538
 
6.0%
0.0417 18090
 
5.9%
0.0833 5131
 
1.7%
0.4167 4068
 
1.3%
0.1667 3570
 
1.2%
0.125 3373
 
1.1%
0 2351
 
0.8%
0.5 1835
 
0.6%
0.6667 1261
 
0.4%
Other values (37) 6915
 
2.2%
ValueCountFrequency (%)
0 2351
 
0.8%
0.0208 50
 
< 0.1%
0.0417 18090
5.9%
0.0625 51
 
< 0.1%
0.0833 5131
 
1.7%
ValueCountFrequency (%)
1 147
< 0.1%
0.9792 5
 
< 0.1%
0.9583 14
 
< 0.1%
0.9167 130
< 0.1%
0.875 16
 
< 0.1%

LANDAREA_MEDI
Real number (ℝ)

Zeros 

Distinct3560
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05620260836
Minimum0
Maximum1
Zeros15919
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:50.134250image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0487
median0.0487
Q30.0487
95-th percentile0.1284
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05314986321
Coefficient of variation (CV)0.9456832122
Kurtosis86.74267328
Mean0.05620260836
Median Absolute Deviation (MAD)0
Skewness7.159261989
Sum17282.9203
Variance0.002824907959
MonotonicityNot monotonic
2024-12-02T17:03:50.552310image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0487 182692
59.4%
0 15919
 
5.2%
0.0193 197
 
0.1%
0.0642 194
 
0.1%
0.0482 186
 
0.1%
0.0143 180
 
0.1%
0.0161 180
 
0.1%
0.0803 179
 
0.1%
0.0241 177
 
0.1%
0.0321 176
 
0.1%
Other values (3550) 107431
34.9%
ValueCountFrequency (%)
0 15919
5.2%
0.0001 14
 
< 0.1%
0.0002 13
 
< 0.1%
0.0003 7
 
< 0.1%
0.0004 11
 
< 0.1%
ValueCountFrequency (%)
1 135
< 0.1%
0.9947 3
 
< 0.1%
0.9858 1
 
< 0.1%
0.9662 1
 
< 0.1%
0.9614 2
 
< 0.1%

LIVINGAPARTMENTS_MEDI
Real number (ℝ)

Distinct1097
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08428166017
Minimum0
Maximum1
Zeros433
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:50.971456image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0333
Q10.0761
median0.0761
Q30.0761
95-th percentile0.1693
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05403232516
Coefficient of variation (CV)0.6410923213
Kurtosis57.42867794
Mean0.08428166017
Median Absolute Deviation (MAD)0
Skewness5.863725071
Sum25917.5376
Variance0.002919492162
MonotonicityNot monotonic
2024-12-02T17:03:51.395183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0761 210824
68.6%
0.0513 4500
 
1.5%
0.0684 4497
 
1.5%
0.077 2926
 
1.0%
0.0599 2708
 
0.9%
0.0855 2014
 
0.7%
0.1231 1921
 
0.6%
0.0068 1715
 
0.6%
0.0616 1691
 
0.5%
0.1026 1517
 
0.5%
Other values (1087) 73198
 
23.8%
ValueCountFrequency (%)
0 433
0.1%
0.0009 117
 
< 0.1%
0.0013 1
 
< 0.1%
0.0017 254
0.1%
0.0021 2
 
< 0.1%
ValueCountFrequency (%)
1 91
< 0.1%
0.9808 2
 
< 0.1%
0.9654 4
 
< 0.1%
0.9509 5
 
< 0.1%
0.9312 5
 
< 0.1%

LIVINGAREA_MEDI
Real number (ℝ)

Distinct5281
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.091688204
Minimum0
Maximum1
Zeros299
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:51.805247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0146
Q10.0749
median0.0749
Q30.0749
95-th percentile0.2358
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.08099895837
Coefficient of variation (CV)0.8834174391
Kurtosis28.22797537
Mean0.091688204
Median Absolute Deviation (MAD)0
Skewness4.377076641
Sum28195.1313
Variance0.006560831258
MonotonicityNot monotonic
2024-12-02T17:03:52.255504image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0749 154431
50.2%
0 299
 
0.1%
0.0548 239
 
0.1%
0.0518 234
 
0.1%
0.052 233
 
0.1%
0.0521 232
 
0.1%
0.0522 225
 
0.1%
0.0519 217
 
0.1%
0.0513 217
 
0.1%
0.0717 212
 
0.1%
Other values (5271) 150972
49.1%
ValueCountFrequency (%)
0 299
0.1%
0.0001 4
 
< 0.1%
0.0002 8
 
< 0.1%
0.0003 10
 
< 0.1%
0.0004 14
 
< 0.1%
ValueCountFrequency (%)
1 149
< 0.1%
0.9988 1
 
< 0.1%
0.996 1
 
< 0.1%
0.9931 8
 
< 0.1%
0.9919 2
 
< 0.1%

NONLIVINGAPARTMENTS_MEDI
Real number (ℝ)

Skewed  Zeros 

Distinct214
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002644358413
Minimum0
Maximum1
Zeros269611
Zeros (%)87.7%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:52.678043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.0097
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02651553358
Coefficient of variation (CV)10.02720866
Kurtosis936.22943
Mean0.002644358413
Median Absolute Deviation (MAD)0
Skewness28.05803955
Sum813.1693
Variance0.0007030735211
MonotonicityNot monotonic
2024-12-02T17:03:53.112615image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 269611
87.7%
0.0039 14126
 
4.6%
0.0078 6493
 
2.1%
0.0116 3788
 
1.2%
0.0155 2557
 
0.8%
0.0194 1696
 
0.6%
0.0019 1286
 
0.4%
0.0233 1202
 
0.4%
0.0272 864
 
0.3%
0.0311 731
 
0.2%
Other values (204) 5157
 
1.7%
ValueCountFrequency (%)
0 269611
87.7%
0.0019 1286
 
0.4%
0.0039 14126
 
4.6%
0.0058 515
 
0.2%
0.0078 6493
 
2.1%
ValueCountFrequency (%)
1 97
< 0.1%
0.9976 4
 
< 0.1%
0.9938 1
 
< 0.1%
0.9782 3
 
< 0.1%
0.9627 2
 
< 0.1%

NONLIVINGAREA_MEDI
Real number (ℝ)

Zeros 

Distinct3323
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01436612967
Minimum0
Maximum1
Zeros60954
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:53.531252image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0031
median0.0031
Q30.0031
95-th percentile0.0742
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04860998338
Coefficient of variation (CV)3.383652
Kurtosis137.1660624
Mean0.01436612967
Median Absolute Deviation (MAD)0
Skewness9.576779681
Sum4417.7429
Variance0.002362930484
MonotonicityNot monotonic
2024-12-02T17:03:53.969869image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0031 170089
55.3%
0 60954
 
19.8%
0.0012 539
 
0.2%
0.0022 478
 
0.2%
0.0037 456
 
0.1%
0.0044 431
 
0.1%
0.0011 421
 
0.1%
0.0043 415
 
0.1%
0.001 401
 
0.1%
0.0029 387
 
0.1%
Other values (3313) 72940
23.7%
ValueCountFrequency (%)
0 60954
19.8%
0.0001 154
 
0.1%
0.0002 81
 
< 0.1%
0.0003 86
 
< 0.1%
0.0004 147
 
< 0.1%
ValueCountFrequency (%)
1 134
< 0.1%
0.9969 1
 
< 0.1%
0.9792 2
 
< 0.1%
0.9789 1
 
< 0.1%
0.9759 5
 
< 0.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:54.212987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 210295
68.4%
3 73830
 
24.0%
4 12080
 
3.9%
1 5687
 
1.8%
2 5619
 
1.8%
2024-12-02T17:03:54.743043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 210295
68.4%
3 73830
 
24.0%
4 12080
 
3.9%
1 5687
 
1.8%
2 5619
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 210295
68.4%
3 73830
 
24.0%
4 12080
 
3.9%
1 5687
 
1.8%
2 5619
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 210295
68.4%
3 73830
 
24.0%
4 12080
 
3.9%
1 5687
 
1.8%
2 5619
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 210295
68.4%
3 73830
 
24.0%
4 12080
 
3.9%
1 5687
 
1.8%
2 5619
 
1.8%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:54.943517image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 154297
50.2%
1 150503
48.9%
2 1499
 
0.5%
3 1212
 
0.4%
2024-12-02T17:03:55.478003image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 154297
50.2%
1 150503
48.9%
2 1499
 
0.5%
3 1212
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 154297
50.2%
1 150503
48.9%
2 1499
 
0.5%
3 1212
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 154297
50.2%
1 150503
48.9%
2 1499
 
0.5%
3 1212
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 154297
50.2%
1 150503
48.9%
2 1499
 
0.5%
3 1212
 
0.4%

TOTALAREA_MODE
Real number (ℝ)

Distinct5116
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08625764899
Minimum0
Maximum1
Zeros582
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:55.852753image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0118
Q10.067
median0.0688
Q30.0703
95-th percentile0.231
Maximum1
Range1
Interquartile range (IQR)0.0033

Descriptive statistics

Standard deviation0.07910992659
Coefficient of variation (CV)0.9171352049
Kurtosis26.94806366
Mean0.08625764899
Median Absolute Deviation (MAD)0.0017
Skewness4.21647975
Sum26525.1759
Variance0.006258380485
MonotonicityNot monotonic
2024-12-02T17:03:56.337634image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0688 148630
48.3%
0 582
 
0.2%
0.057 247
 
0.1%
0.0547 230
 
0.1%
0.055 227
 
0.1%
0.0548 227
 
0.1%
0.0555 227
 
0.1%
0.0551 225
 
0.1%
0.0573 220
 
0.1%
0.0554 220
 
0.1%
Other values (5106) 156476
50.9%
ValueCountFrequency (%)
0 582
0.2%
0.0001 10
 
< 0.1%
0.0002 4
 
< 0.1%
0.0003 24
 
< 0.1%
0.0004 18
 
< 0.1%
ValueCountFrequency (%)
1 155
0.1%
0.9973 1
 
< 0.1%
0.9931 1
 
< 0.1%
0.992 1
 
< 0.1%
0.979 2
 
< 0.1%
Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:56.596463image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters307511
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 156341
50.8%
5 66040
21.5%
6 64815
21.1%
1 9253
 
3.0%
7 5362
 
1.7%
2 2296
 
0.7%
3 1779
 
0.6%
4 1625
 
0.5%
2024-12-02T17:03:57.145320image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 156341
50.8%
5 66040
21.5%
6 64815
21.1%
1 9253
 
3.0%
7 5362
 
1.7%
2 2296
 
0.7%
3 1779
 
0.6%
4 1625
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 307511
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 156341
50.8%
5 66040
21.5%
6 64815
21.1%
1 9253
 
3.0%
7 5362
 
1.7%
2 2296
 
0.7%
3 1779
 
0.6%
4 1625
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Common 307511
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 156341
50.8%
5 66040
21.5%
6 64815
21.1%
1 9253
 
3.0%
7 5362
 
1.7%
2 2296
 
0.7%
3 1779
 
0.6%
4 1625
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307511
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 156341
50.8%
5 66040
21.5%
6 64815
21.1%
1 9253
 
3.0%
7 5362
 
1.7%
2 2296
 
0.7%
3 1779
 
0.6%
4 1625
 
0.5%

EMERGENCYSTATE_MODE
Real number (ℝ)

Zeros 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5335874164
Minimum0
Maximum2
Zeros145755
Zeros (%)47.4%
Negative0
Negative (%)0.0%
Memory size1.2 MiB
2024-12-02T17:03:57.437927image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum2
Range2
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5138226015
Coefficient of variation (CV)0.9629586188
Kurtosis-1.594556216
Mean0.5335874164
Median Absolute Deviation (MAD)0
Skewness0.03293521435
Sum164084
Variance0.2640136658
MonotonicityNot monotonic
2024-12-02T17:03:57.761647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
1 159428
51.8%
0 145755
47.4%
2 2328
 
0.8%
ValueCountFrequency (%)
0 145755
47.4%
1 159428
51.8%
2 2328
 
0.8%
ValueCountFrequency (%)
2 2328
 
0.8%
1 159428
51.8%
0 145755
47.4%

OBS_30_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.417523276
Minimum0
Maximum348
Zeros164931
Zeros (%)53.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:58.133217image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum348
Range348
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.398395406
Coefficient of variation (CV)1.691961922
Kurtosis1426.335795
Mean1.417523276
Median Absolute Deviation (MAD)0
Skewness12.14379639
Sum435904
Variance5.752300524
MonotonicityNot monotonic
2024-12-02T17:03:58.509647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 164931
53.6%
1 48783
 
15.9%
2 29808
 
9.7%
3 20322
 
6.6%
4 14143
 
4.6%
5 9553
 
3.1%
6 6453
 
2.1%
7 4390
 
1.4%
8 2967
 
1.0%
9 2003
 
0.7%
Other values (23) 4158
 
1.4%
ValueCountFrequency (%)
0 164931
53.6%
1 48783
 
15.9%
2 29808
 
9.7%
3 20322
 
6.6%
4 14143
 
4.6%
ValueCountFrequency (%)
348 1
< 0.1%
47 1
< 0.1%
30 2
< 0.1%
29 1
< 0.1%
28 1
< 0.1%

DEF_30_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.14294448
Minimum0
Maximum34
Zeros272345
Zeros (%)88.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:58.835379image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum34
Range34
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4460325557
Coefficient of variation (CV)3.12032025
Kurtosis126.6766484
Mean0.14294448
Median Absolute Deviation (MAD)0
Skewness5.192572496
Sum43957
Variance0.1989450408
MonotonicityNot monotonic
2024-12-02T17:03:59.143782image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 272345
88.6%
1 28328
 
9.2%
2 5323
 
1.7%
3 1192
 
0.4%
4 253
 
0.1%
5 56
 
< 0.1%
6 11
 
< 0.1%
7 1
 
< 0.1%
34 1
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 272345
88.6%
1 28328
 
9.2%
2 5323
 
1.7%
3 1192
 
0.4%
4 253
 
0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
6 11
 
< 0.1%
5 56
< 0.1%

OBS_60_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.400626319
Minimum0
Maximum344
Zeros165687
Zeros (%)53.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:03:59.523916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum344
Range344
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.377224266
Coefficient of variation (CV)1.697258029
Kurtosis1411.229416
Mean1.400626319
Median Absolute Deviation (MAD)0
Skewness12.07515253
Sum430708
Variance5.651195211
MonotonicityNot monotonic
2024-12-02T17:03:59.921834image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 165687
53.9%
1 48870
 
15.9%
2 29766
 
9.7%
3 20215
 
6.6%
4 13946
 
4.5%
5 9463
 
3.1%
6 6349
 
2.1%
7 4344
 
1.4%
8 2886
 
0.9%
9 1959
 
0.6%
Other values (23) 4026
 
1.3%
ValueCountFrequency (%)
0 165687
53.9%
1 48870
 
15.9%
2 29766
 
9.7%
3 20215
 
6.6%
4 13946
 
4.5%
ValueCountFrequency (%)
344 1
< 0.1%
47 1
< 0.1%
30 1
< 0.1%
29 2
< 0.1%
28 1
< 0.1%

DEF_60_CNT_SOCIAL_CIRCLE
Real number (ℝ)

Zeros 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0997167581
Minimum0
Maximum24
Zeros281742
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:00.287451image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3617346501
Coefficient of variation (CV)3.627621445
Kurtosis86.83515507
Mean0.0997167581
Median Absolute Deviation (MAD)0
Skewness5.287339297
Sum30664
Variance0.1308519571
MonotonicityNot monotonic
2024-12-02T17:04:00.610322image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 281742
91.6%
1 21841
 
7.1%
2 3170
 
1.0%
3 598
 
0.2%
4 135
 
< 0.1%
5 20
 
< 0.1%
6 3
 
< 0.1%
7 1
 
< 0.1%
24 1
 
< 0.1%
ValueCountFrequency (%)
0 281742
91.6%
1 21841
 
7.1%
2 3170
 
1.0%
3 598
 
0.2%
4 135
 
< 0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
7 1
 
< 0.1%
6 3
 
< 0.1%
5 20
 
< 0.1%
4 135
< 0.1%

DAYS_LAST_PHONE_CHANGE
Real number (ℝ)

Zeros 

Distinct3773
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-962.8581189
Minimum-4292
Maximum0
Zeros37672
Zeros (%)12.3%
Negative269839
Negative (%)87.7%
Memory size2.3 MiB
2024-12-02T17:04:00.992417image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-4292
5-th percentile-2522
Q1-1570
median-757
Q3-274
95-th percentile0
Maximum0
Range4292
Interquartile range (IQR)1296

Descriptive statistics

Standard deviation826.807226
Coefficient of variation (CV)-0.8587009963
Kurtosis-0.3085699505
Mean-962.8581189
Median Absolute Deviation (MAD)627
Skewness-0.7136089912
Sum-296089463
Variance683610.189
MonotonicityNot monotonic
2024-12-02T17:04:01.424199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37672
 
12.3%
-1 2812
 
0.9%
-2 2318
 
0.8%
-3 1763
 
0.6%
-4 1285
 
0.4%
-5 824
 
0.3%
-6 537
 
0.2%
-7 442
 
0.1%
-8 278
 
0.1%
-476 222
 
0.1%
Other values (3763) 259358
84.3%
ValueCountFrequency (%)
-4292 1
< 0.1%
-4185 1
< 0.1%
-4173 1
< 0.1%
-4153 1
< 0.1%
-4131 1
< 0.1%
ValueCountFrequency (%)
0 37672
12.3%
-1 2812
 
0.9%
-2 2318
 
0.8%
-3 1763
 
0.6%
-4 1285
 
0.4%

FLAG_DOCUMENT_2
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.227491049 × 10-5
Minimum0
Maximum1
Zeros307498
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:01.783774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.006501789045
Coefficient of variation (CV)153.7978193
Kurtosis23650.07691
Mean4.227491049 × 10-5
Median Absolute Deviation (MAD)0
Skewness153.7918174
Sum13
Variance4.227326079 × 10-5
MonotonicityNot monotonic
2024-12-02T17:04:02.100949image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307498
> 99.9%
1 13
 
< 0.1%
ValueCountFrequency (%)
0 307498
> 99.9%
1 13
 
< 0.1%
ValueCountFrequency (%)
1 13
 
< 0.1%
0 307498
> 99.9%

FLAG_DOCUMENT_3
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7100233813
Minimum0
Maximum1
Zeros89171
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:02.425194image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4537519684
Coefficient of variation (CV)0.6390662342
Kurtosis-1.143040848
Mean0.7100233813
Median Absolute Deviation (MAD)0
Skewness-0.9257248975
Sum218340
Variance0.2058908489
MonotonicityNot monotonic
2024-12-02T17:04:02.801646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
1 218340
71.0%
0 89171
29.0%
ValueCountFrequency (%)
0 89171
29.0%
1 218340
71.0%
ValueCountFrequency (%)
1 218340
71.0%
0 89171
29.0%

FLAG_DOCUMENT_4
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.129790479 × 10-5
Minimum0
Maximum1
Zeros307486
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:03.179869image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.009016183217
Coefficient of variation (CV)110.9030207
Kurtosis12295.64002
Mean8.129790479 × 10-5
Median Absolute Deviation (MAD)0
Skewness110.8943644
Sum25
Variance8.129155979 × 10-5
MonotonicityNot monotonic
2024-12-02T17:04:03.575415image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307486
> 99.9%
1 25
 
< 0.1%
ValueCountFrequency (%)
0 307486
> 99.9%
1 25
 
< 0.1%
ValueCountFrequency (%)
1 25
 
< 0.1%
0 307486
> 99.9%

FLAG_DOCUMENT_5
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01511490646
Minimum0
Maximum1
Zeros302863
Zeros (%)98.5%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:03.979398image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1220102228
Coefficient of variation (CV)8.072178491
Kurtosis61.17621478
Mean0.01511490646
Median Absolute Deviation (MAD)0
Skewness7.94832164
Sum4648
Variance0.01488649447
MonotonicityNot monotonic
2024-12-02T17:04:04.399614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 302863
98.5%
1 4648
 
1.5%
ValueCountFrequency (%)
0 302863
98.5%
1 4648
 
1.5%
ValueCountFrequency (%)
1 4648
 
1.5%
0 302863
98.5%

FLAG_DOCUMENT_6
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08805538664
Minimum0
Maximum1
Zeros280433
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:04.802496image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2833758929
Coefficient of variation (CV)3.218155114
Kurtosis6.453170922
Mean0.08805538664
Median Absolute Deviation (MAD)0
Skewness2.907426517
Sum27078
Variance0.08030189666
MonotonicityNot monotonic
2024-12-02T17:04:05.176716image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 280433
91.2%
1 27078
 
8.8%
ValueCountFrequency (%)
0 280433
91.2%
1 27078
 
8.8%
ValueCountFrequency (%)
1 27078
 
8.8%
0 280433
91.2%

FLAG_DOCUMENT_7
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0001918630553
Minimum0
Maximum1
Zeros307452
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:05.637823image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01385015768
Coefficient of variation (CV)72.18772606
Kurtosis5207.135724
Mean0.0001918630553
Median Absolute Deviation (MAD)0
Skewness72.17410795
Sum59
Variance0.0001918268677
MonotonicityNot monotonic
2024-12-02T17:04:05.970017image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307452
> 99.9%
1 59
 
< 0.1%
ValueCountFrequency (%)
0 307452
> 99.9%
1 59
 
< 0.1%
ValueCountFrequency (%)
1 59
 
< 0.1%
0 307452
> 99.9%

FLAG_DOCUMENT_8
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08137595078
Minimum0
Maximum1
Zeros282487
Zeros (%)91.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:06.287564image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2734120489
Coefficient of variation (CV)3.359863035
Kurtosis7.377366974
Mean0.08137595078
Median Absolute Deviation (MAD)0
Skewness3.062240845
Sum25024
Variance0.07475414851
MonotonicityNot monotonic
2024-12-02T17:04:06.586525image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 282487
91.9%
1 25024
 
8.1%
ValueCountFrequency (%)
0 282487
91.9%
1 25024
 
8.1%
ValueCountFrequency (%)
1 25024
 
8.1%
0 282487
91.9%

FLAG_DOCUMENT_9
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003895795598
Minimum0
Maximum1
Zeros306313
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:06.885350image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0622947108
Coefficient of variation (CV)15.99024108
Kurtosis251.6950013
Mean0.003895795598
Median Absolute Deviation (MAD)0
Skewness15.92775453
Sum1198
Variance0.003880630994
MonotonicityNot monotonic
2024-12-02T17:04:07.185784image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 306313
99.6%
1 1198
 
0.4%
ValueCountFrequency (%)
0 306313
99.6%
1 1198
 
0.4%
ValueCountFrequency (%)
1 1198
 
0.4%
0 306313
99.6%

FLAG_DOCUMENT_10
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.276341334 × 10-5
Minimum0
Maximum1
Zeros307504
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:07.485644image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.004771055354
Coefficient of variation (CV)209.5931433
Kurtosis43925.85711
Mean2.276341334 × 10-5
Median Absolute Deviation (MAD)0
Skewness209.5890537
Sum7
Variance2.276296919 × 10-5
MonotonicityNot monotonic
2024-12-02T17:04:07.789333image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307504
> 99.9%
1 7
 
< 0.1%
ValueCountFrequency (%)
0 307504
> 99.9%
1 7
 
< 0.1%
ValueCountFrequency (%)
1 7
 
< 0.1%
0 307504
> 99.9%

FLAG_DOCUMENT_11
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003912055179
Minimum0
Maximum1
Zeros306308
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:08.099105image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.06242406327
Coefficient of variation (CV)15.95684632
Kurtosis250.6281384
Mean0.003912055179
Median Absolute Deviation (MAD)0
Skewness15.89422878
Sum1203
Variance0.003896763675
MonotonicityNot monotonic
2024-12-02T17:04:08.410674image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 306308
99.6%
1 1203
 
0.4%
ValueCountFrequency (%)
0 306308
99.6%
1 1203
 
0.4%
ValueCountFrequency (%)
1 1203
 
0.4%
0 306308
99.6%

FLAG_DOCUMENT_12
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.503832383 × 10-6
Minimum0
Maximum1
Zeros307509
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:08.701339image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.002550257092
Coefficient of variation (CV)392.1160542
Kurtosis153753
Mean6.503832383 × 10-6
Median Absolute Deviation (MAD)0
Skewness392.1147791
Sum2
Variance6.503811233 × 10-6
MonotonicityNot monotonic
2024-12-02T17:04:09.010214image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307509
> 99.9%
1 2
 
< 0.1%
ValueCountFrequency (%)
0 307509
> 99.9%
1 2
 
< 0.1%
ValueCountFrequency (%)
1 2
 
< 0.1%
0 307509
> 99.9%

FLAG_DOCUMENT_13
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.003525077152
Minimum0
Maximum1
Zeros306427
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:09.301596image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05926771807
Coefficient of variation (CV)16.81316905
Kurtosis278.6898227
Mean0.003525077152
Median Absolute Deviation (MAD)0
Skewness16.75374615
Sum1084
Variance0.003512662406
MonotonicityNot monotonic
2024-12-02T17:04:09.610509image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 306427
99.6%
1 1084
 
0.4%
ValueCountFrequency (%)
0 306427
99.6%
1 1084
 
0.4%
ValueCountFrequency (%)
1 1084
 
0.4%
0 306427
99.6%

FLAG_DOCUMENT_14
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002936480321
Minimum0
Maximum1
Zeros306608
Zeros (%)99.7%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:09.911911image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05410976738
Coefficient of variation (CV)18.42674272
Kurtosis335.5521636
Mean0.002936480321
Median Absolute Deviation (MAD)0
Skewness18.37253334
Sum903
Variance0.002927866926
MonotonicityNot monotonic
2024-12-02T17:04:10.221836image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 306608
99.7%
1 903
 
0.3%
ValueCountFrequency (%)
0 306608
99.7%
1 903
 
0.3%
ValueCountFrequency (%)
1 903
 
0.3%
0 306608
99.7%

FLAG_DOCUMENT_15
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.001209712823
Minimum0
Maximum1
Zeros307139
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:10.519499image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03475993883
Coefficient of variation (CV)28.7340418
Kurtosis821.6570635
Mean0.001209712823
Median Absolute Deviation (MAD)0
Skewness28.69933309
Sum372
Variance0.001208253347
MonotonicityNot monotonic
2024-12-02T17:04:10.833102image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307139
99.9%
1 372
 
0.1%
ValueCountFrequency (%)
0 307139
99.9%
1 372
 
0.1%
ValueCountFrequency (%)
1 372
 
0.1%
0 307139
99.9%

FLAG_DOCUMENT_16
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.009928100133
Minimum0
Maximum1
Zeros304458
Zeros (%)99.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:11.134014image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09914416234
Coefficient of variation (CV)9.986217001
Kurtosis95.73580948
Mean0.009928100133
Median Absolute Deviation (MAD)0
Skewness9.886110804
Sum3053
Variance0.009829564926
MonotonicityNot monotonic
2024-12-02T17:04:11.736535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 304458
99.0%
1 3053
 
1.0%
ValueCountFrequency (%)
0 304458
99.0%
1 3053
 
1.0%
ValueCountFrequency (%)
1 3053
 
1.0%
0 304458
99.0%

FLAG_DOCUMENT_17
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0002666571277
Minimum0
Maximum1
Zeros307429
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:12.020922image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01632748874
Coefficient of variation (CV)61.23027305
Kurtosis3745.195328
Mean0.0002666571277
Median Absolute Deviation (MAD)0
Skewness61.21414027
Sum82
Variance0.0002665868886
MonotonicityNot monotonic
2024-12-02T17:04:12.327379image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307429
> 99.9%
1 82
 
< 0.1%
ValueCountFrequency (%)
0 307429
> 99.9%
1 82
 
< 0.1%
ValueCountFrequency (%)
1 82
 
< 0.1%
0 307429
> 99.9%

FLAG_DOCUMENT_18
Real number (ℝ)

Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.008129790479
Minimum0
Maximum1
Zeros305011
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:12.652411image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.08979823611
Coefficient of variation (CV)11.04557815
Kurtosis118.0145348
Mean0.008129790479
Median Absolute Deviation (MAD)0
Skewness10.95507952
Sum2500
Variance0.008063723208
MonotonicityNot monotonic
2024-12-02T17:04:12.970567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 305011
99.2%
1 2500
 
0.8%
ValueCountFrequency (%)
0 305011
99.2%
1 2500
 
0.8%
ValueCountFrequency (%)
1 2500
 
0.8%
0 305011
99.2%

FLAG_DOCUMENT_19
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0005951006631
Minimum0
Maximum1
Zeros307328
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:13.270267image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02438746507
Coefficient of variation (CV)40.98040311
Kurtosis1675.415835
Mean0.0005951006631
Median Absolute Deviation (MAD)0
Skewness40.95613431
Sum183
Variance0.0005947484523
MonotonicityNot monotonic
2024-12-02T17:04:13.569684image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307328
99.9%
1 183
 
0.1%
ValueCountFrequency (%)
0 307328
99.9%
1 183
 
0.1%
ValueCountFrequency (%)
1 183
 
0.1%
0 307328
99.9%

FLAG_DOCUMENT_20
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0005072989259
Minimum0
Maximum1
Zeros307355
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:13.872916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02251762027
Coefficient of variation (CV)44.38728158
Kurtosis1966.256856
Mean0.0005072989259
Median Absolute Deviation (MAD)0
Skewness44.3648968
Sum156
Variance0.0005070432226
MonotonicityNot monotonic
2024-12-02T17:04:14.213542image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307355
99.9%
1 156
 
0.1%
ValueCountFrequency (%)
0 307355
99.9%
1 156
 
0.1%
ValueCountFrequency (%)
1 156
 
0.1%
0 307355
99.9%

FLAG_DOCUMENT_21
Real number (ℝ)

Skewed  Zeros 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0003349473677
Minimum0
Maximum1
Zeros307408
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:14.508167image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.01829853182
Coefficient of variation (CV)54.63106621
Kurtosis2980.592507
Mean0.0003349473677
Median Absolute Deviation (MAD)0
Skewness54.61293914
Sum103
Variance0.0003348362669
MonotonicityNot monotonic
2024-12-02T17:04:14.831720image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 307408
> 99.9%
1 103
 
< 0.1%
ValueCountFrequency (%)
0 307408
> 99.9%
1 103
 
< 0.1%
ValueCountFrequency (%)
1 103
 
< 0.1%
0 307408
> 99.9%

AMT_REQ_CREDIT_BUREAU_HOUR
Real number (ℝ)

Zeros 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.005538013274
Minimum0
Maximum4
Zeros305885
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:15.133915image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0780141305
Coefficient of variation (CV)14.08702483
Kurtosis294.6212259
Mean0.005538013274
Median Absolute Deviation (MAD)0
Skewness15.64198975
Sum1703
Variance0.006086204557
MonotonicityNot monotonic
2024-12-02T17:04:15.461341image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 305885
99.5%
1 1560
 
0.5%
2 56
 
< 0.1%
3 9
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
0 305885
99.5%
1 1560
 
0.5%
2 56
 
< 0.1%
3 9
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
4 1
 
< 0.1%
3 9
 
< 0.1%
2 56
 
< 0.1%
1 1560
 
0.5%
0 305885
99.5%

AMT_REQ_CREDIT_BUREAU_DAY
Real number (ℝ)

Skewed  Zeros 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.006055067949
Minimum0
Maximum9
Zeros306022
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:15.794166image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1030371201
Coefficient of variation (CV)17.01667446
Kurtosis1331.756374
Mean0.006055067949
Median Absolute Deviation (MAD)0
Skewness29.08157716
Sum1862
Variance0.01061664812
MonotonicityNot monotonic
2024-12-02T17:04:16.087199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 306022
99.5%
1 1292
 
0.4%
2 106
 
< 0.1%
3 45
 
< 0.1%
4 26
 
< 0.1%
5 9
 
< 0.1%
6 8
 
< 0.1%
9 2
 
< 0.1%
8 1
 
< 0.1%
ValueCountFrequency (%)
0 306022
99.5%
1 1292
 
0.4%
2 106
 
< 0.1%
3 45
 
< 0.1%
4 26
 
< 0.1%
ValueCountFrequency (%)
9 2
 
< 0.1%
8 1
 
< 0.1%
6 8
 
< 0.1%
5 9
 
< 0.1%
4 26
< 0.1%

AMT_REQ_CREDIT_BUREAU_WEEK
Real number (ℝ)

Zeros 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02972251399
Minimum0
Maximum8
Zeros298975
Zeros (%)97.2%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:16.390531image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum8
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1907279376
Coefficient of variation (CV)6.416951731
Kurtosis192.7339143
Mean0.02972251399
Median Absolute Deviation (MAD)0
Skewness10.00803257
Sum9140
Variance0.03637714618
MonotonicityNot monotonic
2024-12-02T17:04:16.719020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 298975
97.2%
1 8208
 
2.7%
2 199
 
0.1%
3 58
 
< 0.1%
4 34
 
< 0.1%
6 20
 
< 0.1%
5 10
 
< 0.1%
8 5
 
< 0.1%
7 2
 
< 0.1%
ValueCountFrequency (%)
0 298975
97.2%
1 8208
 
2.7%
2 199
 
0.1%
3 58
 
< 0.1%
4 34
 
< 0.1%
ValueCountFrequency (%)
8 5
 
< 0.1%
7 2
 
< 0.1%
6 20
< 0.1%
5 10
 
< 0.1%
4 34
< 0.1%

AMT_REQ_CREDIT_BUREAU_MON
Real number (ℝ)

Zeros 

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2312925391
Minimum0
Maximum27
Zeros263752
Zeros (%)85.8%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:17.060186image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum27
Range27
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8568100736
Coefficient of variation (CV)3.704443199
Kurtosis103.977208
Mean0.2312925391
Median Absolute Deviation (MAD)0
Skewness8.371504668
Sum71125
Variance0.7341235022
MonotonicityNot monotonic
2024-12-02T17:04:17.418172image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 263752
85.8%
1 33147
 
10.8%
2 5386
 
1.8%
3 1991
 
0.6%
4 1076
 
0.3%
5 602
 
0.2%
6 343
 
0.1%
7 298
 
0.1%
9 206
 
0.1%
8 185
 
0.1%
Other values (14) 525
 
0.2%
ValueCountFrequency (%)
0 263752
85.8%
1 33147
 
10.8%
2 5386
 
1.8%
3 1991
 
0.6%
4 1076
 
0.3%
ValueCountFrequency (%)
27 1
 
< 0.1%
24 1
 
< 0.1%
23 1
 
< 0.1%
22 1
 
< 0.1%
19 3
< 0.1%

AMT_REQ_CREDIT_BUREAU_QRT
Real number (ℝ)

Skewed  Zeros 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22963081
Minimum0
Maximum261
Zeros256936
Zeros (%)83.6%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:17.752570image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum261
Range261
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7440589927
Coefficient of variation (CV)3.240240248
Kurtosis49065.99873
Mean0.22963081
Median Absolute Deviation (MAD)0
Skewness141.4009149
Sum70614
Variance0.5536237845
MonotonicityNot monotonic
2024-12-02T17:04:18.077281image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 256936
83.6%
1 33862
 
11.0%
2 14412
 
4.7%
3 1717
 
0.6%
4 476
 
0.2%
5 64
 
< 0.1%
6 28
 
< 0.1%
8 7
 
< 0.1%
7 7
 
< 0.1%
261 1
 
< 0.1%
ValueCountFrequency (%)
0 256936
83.6%
1 33862
 
11.0%
2 14412
 
4.7%
3 1717
 
0.6%
4 476
 
0.2%
ValueCountFrequency (%)
261 1
 
< 0.1%
19 1
 
< 0.1%
8 7
 
< 0.1%
7 7
 
< 0.1%
6 28
< 0.1%

AMT_REQ_CREDIT_BUREAU_YEAR
Real number (ℝ)

Zeros 

Distinct25
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.778463209
Minimum0
Maximum25
Zeros71801
Zeros (%)23.3%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2024-12-02T17:04:18.419567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q33
95-th percentile5
Maximum25
Range25
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.765523148
Coefficient of variation (CV)0.9927240206
Kurtosis2.785446001
Mean1.778463209
Median Absolute Deviation (MAD)1
Skewness1.46564316
Sum546897
Variance3.117071985
MonotonicityNot monotonic
2024-12-02T17:04:18.774092image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 104924
34.1%
0 71801
23.3%
2 50192
16.3%
3 33628
 
10.9%
4 20714
 
6.7%
5 12052
 
3.9%
6 6967
 
2.3%
7 3869
 
1.3%
8 2127
 
0.7%
9 1096
 
0.4%
Other values (15) 141
 
< 0.1%
ValueCountFrequency (%)
0 71801
23.3%
1 104924
34.1%
2 50192
16.3%
3 33628
 
10.9%
4 20714
 
6.7%
ValueCountFrequency (%)
25 1
< 0.1%
23 1
< 0.1%
22 1
< 0.1%
21 1
< 0.1%
20 1
< 0.1%